Stockholm

Ref. No. SU FV-0793-23

Closing date: 15/04/2023

URL to this page
https://www.su.se/english/about-the-university/work-at-su/available-jobs/phd-student-positions-1.507588?rmpage=job&rmjob=20262&rmlang=UK

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We have  currently 2 open postdoc position at the LISN (ex-LIMS). You can apply online
and get more details here:
- multilingual ASR
https://emploi.cnrs.fr/Offres/CDD/UMR9015-LUCOND-003/Default.aspx?lang=EN
- ASR for low computational resource environment
https://emploi.cnrs.fr/Offres/CDD/UMR9015-LUCOND-002/Default.aspx?lang=EN

Feel free to contact me if you have any questions.

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Le service Plateformes du laboratoire GIPSA-LAB (CNRS/G-INP/UGA, Grenoble) recrute un.e ingénieur.e d?étude en instrumentation.
Il/Elle interviendra en support pour les plateformes expérimentales du laboratoire, et en particulier celles en lien avec l'aéro-acoustique, l'automatique ou la robotique. Il/elle aura notamment en charge  la responsabilité technique de la plateforme AERO, dédiée à l'étude des phénomènes aéro-acoustiques de la production de parole : réalisation de l'interfaçage d'instrumentations, gestion et entretien du parc d'appareils de mesures, préparation et participation aux expériences scientifiques.

Pour plus d'information, la fiche de poste détaillée est disponible ici : https://filesender.renater.fr/?s=download&token=2ae39938-121d-44c4-b6ce-385029ecf331

N'hésitez pas à me contacter si besoin d'information complémentaire.

Coriandre VILAIN

-- 
Coriandre Vilain
Ingénieur de Recherche UGA
Equipe PCMD, Pôle Parole & Cognition, GIPSA-LAB 
--
Responsable Service Plateformes GIPSA
--
04 76 82 77 80
www.gipsa-lab.fr/~coriandre.vilain

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Dear All,

Telecom SudParis welcomes applications for a permanent position of Associate-Assistant Professor in artificial intelligence for semantic and multi-modal multimedia analysis. Telecom SudParis is a public graduate school for engineering, which has been recognized on the highest level in the domain of digital technology. Telecom SudParis is co-founder member of the Institut Polytechnique de Paris and part of the Institut Mines-Telecom, the number one group of engineering schools in France. The recruited assistant/associate professor will join the ARTEMIS (Advanced Research and TEchniques for Multidimensional Imaging Systems) Department of Télécom SudParis and the SAMOVAR laboratory. The targeted research theme concerns the field of artificial intelligence, applied to the semantic analysis of massive, distributed and heterogeneous multimedia data. This concerns the automatic, multi-modal interpretation of complex audio-visual documents, computer vision, multimedia indexation, knowledge extraction and machine learning methodologies. The expected contributions will focus on deep neural network learning methods and target the entire multimedia content processing chain. Detailed information can be found at the following URL: https://institutminestelecom.recruitee.com/l/en/o/maitre-de-conferences-en-intelligence-artificielle-pour-lanalyse-semantique-de-donnees-multimedia-cdi The application deadline is March 31, 2023. Please do not hesitate to contact me for any further information.

Best regards,

Titus ZAHARIA, Professor

Head of the ARTEMIS Department Télécom SudParis

Institut Polytechnique de Paris

titus.zaharia@telecom-sudparis.eu

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Title of Project: Deep Cascaded Representation Learning for Speech Modelling

Supervisor:Professor Thomas Hain

Deadline for Applications:13th April 2023

The LivePerson Centre for Speech and Language offers a 3 year fully funded PhD studentship
covering standard maintenance, fees and travel support, to work on cascaded deep learning structures
to model speech. The Centre is connected with the Speech and Hearing (SpandH) and the Natural
Language Processing (NLP) research groups in the Department of Computer Science at the University
of Sheffield.
Auto-encoding is a powerful concept that allows us to compress signals and find essential
representations.Th econcept was expanded to include context, which is usually referred to as
self-supervised learning. On very large amounts of speech data this has led to very successful
methods and models for representing speech data, for a wide range of downstream processes.
Examples of such models are Wave2Vec or WaveLM. Use of their representations often requires
fine-tuning to a specific task, with small amounts of data. When encoding speech, it is desirable to
represent a range of attributes at different temporal specificity. Such attributes often reflect a hierarchy
of information.
The aim in this PhD project is to explore the use of knowledge about natural hierarchies in speech in
cascaded auto- and contextual encoder/decoder models. The objective is to describe a structured way
to understand such hierarchies. The successful candidate is expected to propose methods to combine
different kinds of supervision (auto, context, label) and build hierarchies of embeddings extractions.
These propositions may have to be seen in the context of data availability and complexity. All
proposals are to be implemented and tested on speech data. Experiments should be conducted on a
range of speech data sets with different speech types and data set size.
The student will join a world-leading team of researchers in speech and language technology. The
LivePerson Centre for Speech and Language Technology was established in 2017 with the aim to
conduct research into novel methods for speech recognition and general speech processing, including
end to end modelling, direct waveform modelling and new approaches to modelling of acoustics and
language. It has recently extended its research remit to spoken and written dialogue. The Centre hosts
severa lResearch Associates, PhD researchers,graduate and undergraduate project students,
Researchers and Engineers from LivePerson, and academic visitors. Being fully connected with
SpandH brings collaboration, and access to a wide range of academic research and opportunities for
collaboration inside and outside of the University. The Centre has access to extensive dedicated
computing resources (GPU, large storage) and local storage of over 60TB of raw speech data.

The successful applicant will work under the supervision of Prof. Hain who is the Director of the
LivePerson Centre and also Head of the SpandH research group. SpandH was and is involved in a
large number of national and international projects funded by national bodies and EU sources as well
as industry. Prof. Hain also leads the UKRI Centre for Doctoral Training In Speech and Language
Technologies and their Applications (https://slt-cdt.ac.uk/) - a collaboration between the NLP research
group and SpandH. Jointly, NLP and SpandH host more than 110 active researchers in these fields.
This project will start as soon as possible.
If English is not your first language, you must have an IELTS score of 6.5 overall, with no less than 6.0
in each component.

How to Apply:All applications must be made directly to the University of Sheffield using the
Postgraduate Online Application Form.
Information on what documents are required and a link to the application form can
be found here - https://www.sheffield.ac.uk/postgraduate/phd/apply/applying
On your application, please name Prof. Thomas Hain as your proposed supervisor
and include the title of the studentship you wish to apply for.
Your research proposal should:
●Be no longer than 4 A4 pages, including references
●Outline your reasons for applying for this studentship
●Explain how you would approach the research, including details of your
skills and experience in the topic area
If you have any queries, please contact phd-compsci@sheffield.ac.uk

Funding Details:
This position is fully funded by LivePerson, covering all tuition fees and a stipend at
the standard UKRI rate

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Job Title:Research Associate in Integrated Multitask Neural Speech Labelling
For further information and the link to apply please visit:
https://www.jobs.ac.uk/job/CXH168/research-associate-in-integrated-multitask-neural-speech-
labelling
Deadline for
Applications:15th March 2023
We are seeking an outstanding Research Associate in Integrated Multitask Neural Speech
Labelling, to join the LivePerson Centre for Speech and Language Technology based at the
University of Sheffield, which is linked with the Speech and Hearing (SpandH) research group
in the Department of Computer Science.
Youare applying to join a world-leading team of researchers in speech and language
technology to work on new ways to integrate a variety of speech technology labelling,
clustering or segmentatio ntasks into a single algorithm or process, in the context o fdeep
neural networks.Even end to end(E2E) automatic speech recognition is  typically
considered as a standalone process, independent of other speech audio technology tasks
such as diarisation, acoustic event detection or intent recognition.
The LivePerson Centre for Speech and Language Technology was established in 2017 with
the aim of conducting research into novel methods for speech recognition and general speech
processing, including end to end modelling, direct waveform modelling and new approaches
to modelling of acoustics and language. It has recently extended its research remit to spoken
and written dialogue. The Centre hosts several Research Associates, PhD researchers,
graduate and undergraduate project students, Researchers and Engineers from LivePerson,
and academic visitors, which will provide avibrant work environmentwithin the University.
Being fully connected with SpandH brings collaboration, and access to a wide range of
academic research and opportunities for collaboration inside and outside of the University.
Thepostholder wil lwork closely with Prof.Thomas Hain who is the Director of the
LivePerson Centre and also Head of the SpandH group. Prof. Hain also leads the UKRI
Centre for Doctora lTraining InSpeech and LanguageTechnologies and their
Applications(slt-cdt.ac.uk) - a collaboration between the Natural Language Processing
(NLP) research group and SpandH. Jointly, NLP and SpandH host more than 110 active
researchers in these fields.

We’re one of the best not-for-profit organisations to work for in the UK. The University’s Total
Reward Package includes a competitive salary, a generous Pension Scheme and annual
leave entitlement, as well as access to a range of learning and development courses to
support your personal and professional development.
We build teams of people from different heritages and lifestyles from across the world, whose
talent and contributions complement each other to the greatest effect. We believe diversity in
all its forms delivers greater impact through research, teaching and student experience.
To find out what makes the University of Sheffield a remarkable place to work, watch this short
film: www.youtube.com/watch?v=7LblLk18zmo, and follow @sheffielduni and @ShefUniJobs
on Twitter for more information.

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Title of Project: PhD Position in Adaptive Deep Learning for Speech and Language

Supervisor:Professor Thomas Hain
Deadline for
Applications:13th April 2023
The LivePerson Centre for Speech and Language offers a 3 year fully funded PhD studentship
covering standard maintenance, fees and travel support, to work on deep neural network adaptive
learning modules for speech and language. The Centre is connected with the Speech and Hearing
(SpandH) and the Natural Language Processing(NLP) researchg roups at the Department  of
Computer Science at the University of Sheffield.
Domain mismatch remains a key issue for speech and language technologies for which traditional
solutions are transfer learning and adaptation. The latter was widely used for modelling of speech in
the context of generative models, however less so with modern neural network approaches. Such
adaptation targeted features or models and was often informed by previous model output and
estimates of latent factors. These approaches were often informed by observations on human abilities
to adapt and adjust to new acoustic or semantic situations. Adaptation in neural networks is model
based and often implicit - through attention or dynamic convolution. However, these methods to date
still fail to reproduce the rapid learning and adaptation that humans exhibit when being exposed to new
contexts.
The objective in this project is to conduct research into neural network structures that are capable of
rapidly adjusting to a change in latent factors and at the same time allow for robust control. This will
require rapid feedback mechanisms on the mismatch between the observed data and the model
expectation. A range of strategies may be applied - through instantaneous feedback or through control
of transformational model parameters. All proposals are to be implemented and tested on speech, and
where suitable, also language data. Experiments should be conducted on a range of tasks of different
complexity in the context of different data types.
The student will join a world-leading team of researchers in speech and language technology. The
LivePerson Centre for Speech and Language Technology was established in 2017 with the aim to
conduct research into novel methods for speech recognition and general speech processing, including
end-to-end modelling, direct waveform modelling and new approaches to modelling of acoustics and
language. It has recently extended its research remit to spoken and written dialogue. The Centre hosts
severalResearchAssociates,PhDresearchers,graduateandundergraduateprojectstudents,
ResearchersandEngineers from LivePerson, and academic visitors. Being fully connected with
SpandH brings collaboration, and access to a wide range of academic research and opportunities for
collaboration inside and outside of the University. The Centre has access to extensive dedicated
computing resources (GPU, large storage) and local storage of over 60TB of raw speech data

The successful applicant will work under the supervision of Prof. Hain who is the Director of the
LivePerson Centre and also Head of the SpandH research group. SpandH was and is involved in a
large number of national and international projects funded by national bodies and EU sources as well
as industry. Prof. Hain also leads the UKRI Centre for Doctoral Training In Speech and Language
Technologies and their Applications (https://slt-cdt.ac.uk/) - a collaboration between the NLP research
group and SpandH. Jointly, NLP and SpandH host more than 110 active researchers in these fields.
This project will start as soon as possible.
If English is not your first language, you must have an IELTS score of 6.5 overall, with no less than 6.0
in each component.
How to Apply:All applications must be made directly to the University of Sheffield using the
Postgraduate Online Application Form.
Information on what documents are required and a link to the application form can
be found here - https://www.sheffield.ac.uk/postgraduate/phd/apply/applying
On your application, please name Prof. Thomas Hain as your proposed supervisor
and include the title of the studentship you wish to apply for.
Your research proposal should:
●Be no longer than 4 A4 pages, including references
●Outline your reasons for applying for this studentship
●Explain how you would approach the research, including details of your
skills and experience in the topic area
If you have any queries, please contact phd-compsci@sheffield.ac.uk
Funding
Details:
This position is fully funded by LivePerson, covering all tuition fees and a stipend at
the standard UKRI rate.

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Deux postes de MCF en phonétique sont ouverts au concours à l'Université Paul-Valéry Montpellier 3 cette année :

Phonétique générale et traitement outillé de l'oral (UMR 5267 Praxiling) : https://www.galaxie.enseignementsup-recherche.gouv.fr/ensup/ListesPostesPublies/ANTEE/2023_1/0341089Z/FOPC_0341089Z_4352.pdf

Phonétique et Didactique de l'oral en FLE (acquisition / appropriation des langues) : https://www.galaxie.enseignementsup-recherche.gouv.fr/ensup/ListesPostesPublies/ANTEE/2023_1/0341089Z/FOPC_0341089Z_4353.pdf

Date limite : 30 mars 2023

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Stockholm

Ref. No. SU FV-0793-23

Closing date: 15/04/2023

URL to this page
https://www.su.se/english/about-the-university/work-at-su/available-jobs/phd-student-positions-1.507588?rmpage=job&rmjob=20262&rmlang=UK

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The Department of Linguistics at Stockholm University invites applications for a PhD student position in experimental phonetics, including (but not limited to) topics in prosody. For details, see: https://www.su.se/english/about-the-university/work-at-su/available-jobs/phd-student-positions-1.507588?rmpage=job&rmjob=20262&rmlang=UK .

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The Digital Linguistics Lab at Bielefeld University (head: JProf. Dr.-Ing. Hendrik Buschmeier) is seeking to fill a research position (PhD-student, E13 TV-L, 100%, fixed-term) in the area of multimodal human-robot interaction in the research project ?Hybrid Living?.

Join us to work in an interdisciplinary team on research questions in the intersection of human-robot interaction and computational linguistics. Specifically, you will work (1) on the use of multimodal communication (verbal and nonverbal) to situatively instruct a service robot, (2) on making the robot's behaviour transparent to its users, and (3) on models for solving human-robot interaction problems through communication.

The formal job advertisement, with information on how to apply, can be found here: https://uni-bielefeld.hr4you.org/job/view/2265/research-position-in-multimodal-human-robot-interaction?page_lang=en

Questions? Don't hesitate to get in touch: hbuschme@uni-bielefeld.de

Hendrik Buschmeier

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We are seeking a multimodal designer to take on a central role in the Shared Reality Lab?s open source IMAGE project (image.a11y.mcgill.ca), focused on making photos, charts, and maps available to people who are blind or low vision. We are currently operating under two grants, focused on integrating haptic force feedback and pin array devices into IMAGE. You will work with a multidisciplinary team of user experience researchers, designers, and developers who will support you in designing and releasing multimodal audio and haptic experiences that will delight our end users. The primary requirement is a strong background and passion for owning both design and iterative testing of combined audio/haptic end-user experiences. Since the goal of IMAGE is to release a practical solution that can be used on a daily basis, the candidate will work directly with developers and the rest of the team to make sure that ideas and designs get translated into implementable requirements, then deployed into production.

Requirements:

• Demonstrated experience designing and creating multimodal experiences, including audio and haptics. Please include portfolio, or links to projects.
• Ability to work with user experience researchers to clearly define user needs and specific implementation requirements to meet them.
• Comfortable working directly with developers to make sure the experiences are implementable within the project timeline and available resources.
• Prototyping experience.
• Designing and carrying out methodologically sound user testing in consultation with our existing user studies lead.
• Strong plus: Sensitization to development issues, software release cycles, software architecture, client-server tradeoffs, audio synthesis.
• Bonus: French, spoken and/or written.
• Bonus: Experience working with the blind/low vision community.

Other useful skills (not required). If the candidate has the desire and capability, they are also welcome to participate in software architecture and implementation, for example:

• Audio synthesis experience. (IMAGE currently uses SuperCollider)
• Software architecture, design, and documentation, including creating usable solutions for developers and content creators in a client/server model.
• Mentoring junior designers/developers.

Candidates applying as a research assistant must be eligible to work in Canada.

Those applying as postdoctoral candidates should refer to McGill?s requirements on postdoctoral appointments, www.mcgill.ca/gps/postdocs, for conditions and additional information on the status of the position. (In Quebec, a Postdoctoral Fellow is a full-time student status and trainee category, and the Ministère de l'Education, Enseignement Supérieur et Recherche (MESRS) stipulates that all postdocs must be registered on a university student registration system.) Please note that non-Canadian postdoctoral fellows must obtain valid Citizenship or an Immigration Canada (CIC) work permit to legally work in Canada.

To apply for the position, please email the following items to Jeremy Cooperstock (srl-jobs@cim.mcgill.ca):

• A brief letter of application, describing your qualifications and relevant experience to the position of interest, along with your dates of availability.
• Detailed CV with links to online papers and/or project portfolios.
• Two (2) reference letters (sent separately).

The position is available immediately, with an initial appointment of up to one year. Informal inquiries are welcome.

About us: The Shared Reality Lab conducts research in audio, video, and haptic technologies, building systems that leverage their capabilities to facilitate and enrich both human-computer and computer-mediated human-human interaction. The lab is part of the Centre for Intelligent Machines and Department of Electrical and Computer Engineering of McGill University. McGill, one of Canada's most prestigious universities, is located in Montreal, a top city to live in, especially for students.
 
McGill University is committed to equity in employment and diversity. It welcomes applications from Aboriginal persons, persons with disabilities, ethnic minorities, persons of minority sexual orientation or gender identity, visible minorities, women and others who may contribute to diversification. All qualified applicants are encouraged to apply, although Canadians and permanent residents will be given priority.

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We have an open 4yr PhD position in the SPEAC labhttps://hrbosker.github.io (Speech Perception in Audiovisual Communication) at the Donders Institute, Radboud University, Nijmegen, The Netherlands.

The position is funded through an ERC Starting Grant (HearingHands, 101040276) awarded to Dr. Hans Rutger Bosker. We are looking for candidates with a strong background in speech perception and an interest in audiovisual prosody and gesture-speech integration.

You will work closely with Dr. Hans Rutger Bosker (PI) and Prof. James McQueen (promotor). The PhD project aims to determine how and when the timing of seemingly meaningless up-and-down hand gestures influences audiovisual speech perception, specifically targeting more naturalistic communicative settings. You will use virtual avatars, allowing careful control of their gestural movements, to establish which kinematic and communicative properties of hand gestures influence low-level speech perception. You will assess how challenging listening conditions impact the perceptual weighting of visual, auditory and audiovisual cues to prominence, as well as determine the time-course of these cues using eye-tracking. Finally, you will design training studies to test how humans adjust their perception to between-talker variation in gesture-speech alignment.

- 4 year contract, 1.0 FTE

- gross monthly salary: ? 2,541 - ? 3,247 (scale P)

- application deadline: May 22, 2023

- preferred starting date: September 1, 2023

More details about the project, profile, and what we have to offer is available through the link below. If you have any questions, do get in touch at HansRutger.Bosker@donders.ru.nl

https://www.ru.nl/en/working-at/job-opportunities/phd-candidate-audiovisual-speech-perception-at-the-donders-centre-for-cognition

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University of Washington, Seattle, WA, USA

Laboratory for Speech Physiology and Motor Control 

Post-doctoral position in speech sensorimotor learning in typical adults,

DBS patients, and adults who stutter

The Laboratory for Speech Physiology and Motor Control (PI Ludo Max, Ph.D.) at the University of Washington (Seattle) is seeking to fill a post-doctoral position in the areas of sensorimotor integration and sensorimotor learning for speech production. The position will involve experimental work on sensorimotor adaptation, sensory prediction, and error evaluation in typical adults, Parkinson’s and essential tremor patients with deep brain stimulation implants (DBS), and adults who stutter. The lab is located in the University of Washington's Department of Speech and Hearing Sciences and has additional affiliations with the Graduate Program in Neuroscience, the Department of Bioengineering, and the Department of Linguistics.

The successful candidate will use speech sensorimotor adaptation paradigms (with digital signal processing perturbations applied to the real-time auditory feedback or mechanical loads applied to the jaw by a robotic device) to investigate various aspects of motor learning and control. Data collection will involve acoustic, kinematic, and neural data to investigate auditory-motor interactions during speech movement planning and execution.

The appointment is initially for one year, with renewal possible contingent upon satisfactory performance and productivity. We are looking for a candidate available to start in the summer of 2023, and applicants should have completed all requirements for their Ph.D. degree by that time. Review of applications will begin immediately. Candidates with a Ph.D. degree in neuroscience, cognitive/behavioral neuroscience, motor control/kinesiology, biomedical engineering, communication disorders/speech science, and related fields, are encouraged to apply.

For more information, please contact lab director Ludo Max, Ph.D. (LudoMax@uw.edu). Applications can be submitted to the same e-mail address. Interested candidates should submit (a) a cover letter describing their research experiences, interests, and goals, (b) a curriculum vitae, (c) the names and contact information of three individuals who can serve as references, and (d) reprints of relevant journal publications.

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Dans le cadre d'un projet PIA, nous avons trois offres de post-doc d'une durée de 2 ans,
ouvertes sur le site toulousain : reconnaissance automatique de la parole, analyse de
sentiments et modélisation de préférences, pour un assistant vocal embarqué dans les
véhicules.

Plus d'info ici : https://www.irit.fr/~Thomas.Pellegrini/pdf/postdoc_3offers_2023.pdf

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Offre d’emploi : 1 Chargé.e de recherche et développement (H/F) Conversion neuronale de l’identité vocale pour la réalisation d’attaques adverses

Disponibilité et durée : 18 mois, de préférence à partir du 01 juin 2023

Description du poste: Dans le cadre du projet ANR BRUEL (2022-2026), l’équipe Analyse et Synthèse des sons recherche un.e chargé.e de recherche pour la conception, l’implémentation, et l’apprentissage d’algorithmes de conversion neuronale de l’identité vocale pour la création d’attaques d’usurpation d’identité. A partir d’un ensemble de scénarios d’attaques envisagées pour réaliser ces attaques en fonction des moyens et ressources disponibles (expertise, algorithmes, données), les travaux consisteront dans un premier temps à réaliser l’implémentation d’un banc d’essais d’algorithmes pour évaluer la robustesse des systèmes d’authentification et de détection face à ces attaques. Les travaux porteront dans un second temps sur l’une ou plusieurs des problématiques suivantes : - L’apprentissage de la conversion d’identité à partir de données de qualité hétérogène et dégradée (compression, bruits, etc…) librement accessibles (par exemple sur internet), et le transfert d’identité à partir de peu de données par des stratégies d’adaptation neuronale à partir de peu d’exemples; - La génération de conversions avec un contrôle de l’emprunte acoustique pour que l’attaque soit adaptée à l’environnement sonore et au canal de communication en fonction des scénarios envisagés (depuis des conditions professionnelles jusqu’à des conditions dégradées de communication téléphonique ou internet). L’ensemble des travaux réalisés seront évalués selon les protocoles usuels en conversion d’identité vocale, mais également en relation avec les partenaires du projet pour mesurer les performances des systèmes d’authentification/détection en fonction des scénarios envisagés. Les avancées réalisées seront intégrées au système de conversion neuronale de l'identité vocale de l’Ircam et évaluées in situ dans le cadre de productions professionnelles et/ou artistiques réalisées à l’Ircam. Le.a chargé.e de recherche collaborera également avec l’équipe de développement et participera aux activités du projet (évaluation des algorithmes, réunions, spécifications, livrables, rapports).

Présentation du projet BRUEL Le projet ANR BRUEL (ElaBoRation d’Une méthodologie d’EvaLuation des systèmes d’identification par la voix) concerne l’évaluation/certification des systèmes d’identification par la voix face aux attaques adverses. En effet, les systèmes de reconnaissance automatique du locuteur sont vulnérables non seulement à la parole produite artificiellement par synthèse vocale, mais aussi à d'autres formes d'attaques telles que la conversion d’identité vocale et la relecture. Les artefacts créés lors de la création ou la manipulation de ces attaques frauduleuses constituent les marques laissées dans le signal par les algorithmes de synthèse vocale permettant ainsi de distinguer la voix réelle originale d’une voix usurpée. Dans ces conditions, la détection de l'usurpation d'identité requiert d'évaluer les contre-mesures d'usurpation d'identité en même temps que les systèmes de reconnaissance du locuteur. Le projet BRUEL ambitionne de proposer la première méthodologie d’évaluation/certification des systèmes d'identification par la voix basée sur une approche Critères Communs.

Contexte de travail Le travail sera effectué à l’IRCAM au sein de l’équipe Analyse et Synthèse des sons encadré par Nicolas Obin et Axel ROEBEL (SU, CNRS, IRCAM). Le travail pourra être mené partiellement à distance, avec la nécessité d’une participation aux réunions d’avancement du projet. L'Ircam est une association à but non lucratif, associée au Centre National d'Art et de Culture Georges Pompidou, dont les missions comprennent des activités de recherche, de création et de pédagogie autour de la musique du XXème siècle et de ses relations avec les sciences et technologies. Au sein de l'unité mixte de recherche, UMR 9912 STMS (Sciences et Technologies de la Musique et du Son) commune à l’Ircam, à Sorbonne Université, au CNRS, et au Ministère de la Culture et de la Communication, des équipes spécialisées mènent des travaux de recherche et de développement informatique dans les domaines de l'acoustique, du traitement des signaux sonores, des sciences cognitives, des technologies d’interaction, de l’informatique musicale et de la musicologie.

L'Ircam est situé au centre de Paris à proximité du Centre Georges Pompidou au 1, Place Stravinsky 75004 Paris.

Expérience et compétences requises: Nous recherchons un.e candidat.e spécialisé.e en apprentissage de réseaux de neurones profonds et en traitement automatique de la parole ou en vision, de préférence en deep fakes. Le·a candidate devra avoir une thèse de doctorat en sciences informatiques dans les domaines de l’apprentissage par réseaux de neurones profonds, ainsi que des publications dans des conférences et revues reconnues dans le domaine. Le·a candidat·e idéal·e aura:

• Une solide expertise en apprentissage machine, et en particulier en réseaux de neurones profonds.

• Une bonne expérience en traitement automatique de la parole ; de préférence dans le domaine de la génération ou des deep-fakes;

• Maîtrise du traitement du signal audio-vidéo numérique;

• Une excellente maîtrise du langage de programmation Python, de l’environnement TensorFlow pour l’apprentissage de réseaux de neurones, et du calcul distribué sur des serveurs GPUs

• Excellente maîtrise de l’anglais scientifique parlé et écrit

• Autonomie, travail en équipe, productivité, rigueur et méthodologie

Salaire Selon formation et expérience professionnelle

Candidatures Prière d'envoyer une lettre de motivation et un CV détaillant le niveau d'expérience/expertise dans les domaines mentionnés ci-dessus (ainsi que tout autre information pertinente) à Nicolas.Obin@ircam.fr et Axel.Roebel@ircam.fr Date limite de candidature 31 mai 2023

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Offre d’emploi : 1 Chargé.e de recherche et développement (H/F) Génération de deep fakes audio-visuel

Disponibilité et durée : 15 mois, de préférence à partir du 01 juin 2023

Description du poste Dans le cadre du projet ASTRID DeTOX (2023-2025), l’équipe Analyse et Synthèse des sons recherche un.e chargé.e de recherche pourl’implémentation et l’apprentissage d’algorithmes pour la génération de deep fakes audio-visuels avec les missions suivantes : - Collection, implémentation, et apprentissage d’algorithmes représentatifs de l’état-del’art pour la génération de deep fakes audio et visuel - Implémentation d’un nouvel algorithme de génération de deep fakes audio-visuel avec synchronisation des deux modalités en particulier pour assurer la cohérence de la parole et du mouvement du lèvre et du bas du visage - Construction de bases de données audio-visuel des personnes ciblées et apprentissage de modèles de génération de deep fakes pour ces personnes Le.a chargé.e de recherche collaborera également avec l’équipe de développement et participera aux activités du projet (évaluation des algorithmes, réunions, spécifications, livrables, rapports). Présentation du projet DeTOX Les récents challenges ont montré qu'il était extrêmement difficile de mettre au point des détecteurs universels de vidéos hyper-truquées - à l'exemple des 'deep fakes' utilisés pour contrefaire l'identité d'une personne. Lorsque les détecteurs sont exposés à des vidéos générées par un algorithme nouveau, c'est-à-dire inconnu lors de la phase d'apprentissage, les performances sont encore extrêmement limitées. Pour la partie vidéo, les algorithmes examinent les images une par une, sans tenir compte de l'évolution de la dynamique faciale au cours du temps. Pour la partie vocale, la voix est générée de manière indépendante de la vidéo ; en particulier, la synchronisation audio-vidéo entre la voix et les mouvements des lèvres n'est pas prise en compte. Ceci constitue un point faible important des algorithmes de génération de vidéos hyper-truquées. Le présent projet vise à implémenter et à apprendre des algorithmes de détection de deepfakes personnalisés sur des individus pour lesquels on peut disposer et/ou fabriquer de nombreuses séquences audio-vidéo réelles et falsifiées. En se basant sur des briques technologiques de base en audio et vidéo récupérées de l'état de l'art, le projet se concentrera sur la prise en compte de l'évolution temporelle des signaux audio-visuels et de leur cohérence pour la génération et la détection. Nous souhaitons ainsi démontrer qu'en utilisant simultanément l’audio et la vidéo et en se focalisant sur une personne précise lors de l'apprentissage et de la détection, il est possible de concevoir des détecteurs efficaces même face à des générateurs encore non répertoriés. De tels outils permettront de scruter et de détecter sur le web d'éventuelles vidéos hyper-truquées de personnalités françaises importantes (président de la république, journalistes, chef d'étatmajor des armées, ...) et ce dès leur publication.

Contexte de travail Le travail sera effectué à l’IRCAM au sein de l’équipe Analyse et Synthèse des sons encadré par Nicolas Obin et Axel ROEBEL (SU, CNRS, IRCAM). Le travail pourra être mené partiellement à distance, avec la nécessité d’une participation aux réunions d’avancement du projet. L'Ircam est une association à but non lucratif, associée au Centre National d'Art et de Culture Georges Pompidou, dont les missions comprennent des activités de recherche, de création et de pédagogie autour de la musique du XXème siècle et de ses relations avec les sciences et technologies. Au sein de l'unité mixte de recherche, UMR 9912 STMS (Sciences et Technologies de la Musique et du Son) commune à l’Ircam, à Sorbonne Université, au CNRS, et au Ministère de la Culture et de la Communication, des équipes spécialisées mènent des travaux de recherche et de développement informatique dans les domaines de l'acoustique, du traitement des signaux sonores, des sciences cognitives, des technologies d’interaction, de l’informatique musicale et de la musicologie.

L'Ircam est situé au centre de Paris à proximité du Centre Georges Pompidou au 1, Place Stravinsky 75004 Paris.

Expérience et compétences requises Nous recherchons un.e candidat.e spécialisé.e en apprentissage de réseaux de neurones profonds et en traitement automatique de la parole ou en vision, de préférence en deep fakes. Le·a candidate devra avoir une thèse de doctorat en sciences informatiques dans les domaines de l’apprentissage par réseaux de neurones profonds, ainsi que des publications dans des conférences et revues reconnues dans le domaine. Le·a candidat·e idéal·e aura:

• Une solide expertise en apprentissage machine, et en particulier en réseaux de neurones profonds.

• Une bonne expérience en traitement automatique de la parole ou en vision ; de préférence dans le domaine des deep-fakes;

• Maîtrise du traitement du signal audio-vidéo numérique;

• Une excellente maîtrise du langage de programmation Python, de l’environnement TensorFlow pour l’apprentissage de réseaux de neurones, et du calcul distribué sur des serveurs GPUs

• Excellente maîtrise de l’anglais scientifique parlé et écrit

• Autonomie, travail en équipe, productivité, rigueur et méthodologie

Salaire Selon formation et expérience professionnelle

Candidatures Prière d'envoyer une lettre de motivation et un CV détaillant le niveau d'expérience/expertise dans les domaines mentionnés ci-dessus (ainsi que tout autre information pertinente) à Nicolas.Obin@ircam.fr et Axel.Roebel@ircam.fr Date limite de candidature 31 mai 2023

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PhD Title: SUMMA-Sound : SUMMarization of Activities of daily living using Sound-based activity recognition Partnership:

IMT Atlantique : Campus ☒ Brest ☐ Nantes ☐ Rennes Laboratory : Lab-STICC Doctoral school : ☒ SPIN ☐ 3MG Funding: IMT Atlantique, co-tutelle with Instituto Superior Técnico

Context : IMT Atlantique, internationally recognised for the quality of its research, is a leading general engineering school under the aegis of the French Ministry of Industry and Digital Technology, ranked in the three main international rankings (THE, SHANGHAI, QS). Located on three campuses, Brest, Nantes and Rennes, IMT Atlantique aims to combine digital technology and energy to transform society and industry through training, research and innovation. It aims to be the leading French higher education and research institution in this field on an international scale. With 290 researchers and permanent lecturers, 1000 publications and 18 M€ of contracts, it supervises 2300 students each year and its training courses are based on cutting-edge research carried out within 6 joint research units: GEPEA, IRISA, LATIM, LABSTICC, LS2N and SUBATECH. The proposed thesis is part of the research activities of the team RAMBO (Robot interaction, Ambient systems, Machine learning, Behaviour, Optimization) and of the laboratory Lab-STICC and the department of Computer Science of IMT Atlantique. Scientific context: The objective of this thesis is to develop a method for collecting and summarizing domestic health-related data relevant for medical diagnosis, in a non-intrusive manner using audio information. This research addresses the lack of existing practical tools for providing high-level succinct information to medical staff on the evolution of patients they follow for health diagnostic purposes. This research is based on the assumption that valuable diagnostic data can be collected by observing short- and long-term lifestyle changes and behavioural anomalies. It relies on the latest advances in the domains of audio-based activity recognition, summarization of human activity, and health diagnosis. Research on health diagnosis in domestic environments has already explored a variety of sensors and modalities for gathering data on human health indicators [5]. Nevertheless, audio-based activity recognition is notable for its less intrusive nature. Employing state-of-the-art sound-based activity recognition models [2] to monitor domestic human activity, the thesis will investigate and develop methods for summarization of human activity [3] in a human-understandable language, in order to produce easily interpretable data by doctors who, remotely, monitor their patients [4]. This work continues and fosters the research of the RAMBO team at IMT Atlantique on ambient systems, enabling well ageing at home for the elderly adults or dependent populations [1]. We expect this thesis to provide technology likely to relieve the burden on gerontologists and elderly-care facilities, and alleviate the caregiver shortage by offering some automatic support to the task of monitoring elderly or handicapped people, enabling them to age-at-home while still being followed by medical specialists using automated means. Expected contributions of the thesis Scientific goals: (1) Determine the set of human activities relevant for health diagnosis, (2) Implement a state-of-the-art model for audio-based activity recognition and validate its function by clinicians, (3) Develop a model for summarizing the evolution of human activity over time intervals of arbitrary duration (typically spanning from days to months and possibly years). Expected outcomes of the PhD: (1) A model for semantic summarization of human activity, based on sound recognition of activities of daily living. (2) A proof of concept for this model Candidate profile and required skills: • Master Degree in Computer Science (or equivalent) • Programming and Software Engineering skills (Python, Git, Software Architecture Design) • Data science skills • Machine learning skills • English speaking and writing skills References: [1] Damien Bouchabou. “Human activity recognition in smart homes : tackling data variability using context-dependent deep learning, transfer learning and data synthesis”. Theses. Ecole nationale supérieure Mines-Télécom Atlantique, May 2022. url: https://theses.hal.science/tel-03728064. [2] Detection and Classification of Acoustic Scenes and Events (DCASE). url: https://dcase.community/challenge2022/task-soundevent-detection-in-domestic-environments (visited on 07/01/2022). [3] P Durga et al. “When less is better: A summarization technique that enhances clinical effectiveness of data”. In: Proceedings of the 2018 International Conference on Digital Health. 2018, pp. 116–120. [4] Akshay Jain et al. “Linguistic summarization of in-home sensor data”. In: Journal of Biomedical Informatics 96 (2019), p. 103240. issn: 1532-0464. [5] Mostafa Haghi Kashani et al. “A systematic review of IoT in healthcare: Applications, techniques, and trends”. In: Journal of Network and Computer Applications 192 (2021), p. 103164. Work Plan: The thesis will be organised in the following steps: (1) Definition of pertinent sounds and activities for health diagnosis, (2) Hardware set-up, (3) Dataset constitution, (4) Activity recognition, (5) Diarization of activities, (6) Summarization, (7) Validation in a real environment. Application: To apply for this position, please send an email with your Curriculum Vitae, a document with your academic results (if possible), and a couple of lines describing your motivation to pursue a PhD to mihai[dot]andries[at]imt-atlantique[dot]fr before 16 May 2023. Additional Information :  Application deadline : 16 May 2023  Start date : Fall 2023  Contract duration: 36 months  Localisation - Location : Brest (France) and Lisbon (Portugal)  Contact(s) : Mihai ANDRIES (mihai[dot]andries[at]imt-atlantique.fr) Plinio Moreno (plinio[at]isr.tecnico.ulisboa.pt)

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We are looking for a PhD student who is interested in Artificial Intelligence, Machine Learning, Natural Language Processing and Human-Robot Interaction.  The doctoral student will work in a newly funded project at the  Department of Speech, Music and Hearing within the School of Electrical Engineering and Computer Science at KTH. The project is financed by the Swedish AI-program WASP (Wallenberg AI, Autonomous Systems and Software Program) which offers a graduate school with research visits, partner universities, and visiting lecturers.

The newly started project is titled 'Anticipatory Control in Conversational Human-Robot Interaction'. The aim of the project is to use self-supervised learning to develop generic language models for human-robot interaction and explore how such models can be used in real time to predict and anticipate human behavior and thereby improve the interaction. Whereas traditional language models in NLP (such as BERT, GPT) have focused on written language, we want to model multi-modal conversation, where aspects such as engagement, turn-taking, and incremental processing are of importance. This means that the models will have to process both text, audio and video, including aspects such as how the human users move and their facial expressions.

In collaboration with industry and other projects, we will then explore how such models can be used for social robotic applications. Another important focus will be on model analysis and visualization.

For more information about the position, see https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:623390/where:4/

If you have any questions, don’t hesitate to contact Prof. Gabriel Skantze

(skantze@kth.se)

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Nous proposons une offre de thèse en acoustique-aérodynamique-mécatronique de la parole, dans le cadre du projet ANR AVATARS (« Artificial Voice production: control of bio-inspired port-HAmilToniAn numeRical and mechatronic modelS », 2023-2027). Le sujet porte sur la  'Caractérisation du comportement vocal humain dans la parole et dans le chant sur banc mécatronique robotisé. Application au développement de plis vocaux biomimétiques.'

Pour plus d'information et pour candidater :
https://www.gipsa-lab.grenoble-inp.fr/~nathalie.henrich/docs/PhDposition_ANR-AVATARS_GIPSA_2023.pdf

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Nous recherchons pour l'année 2023-2024 une personne pour un CDD 50% enseignement et
recherche en Phonétique.

Les infos sont à retrouver ici:
https://emploi.univ-grenoble-alpes.fr/offres/enseignants-enseignants-chercheurs-contractuels/enseignant-e-chercheur-e-en-phonetique-1240660.kjsp?RH=TLK_CDD_ENS

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Nous recherchons un·e candidat·e pour une thèse sur la modélisation computationnelle du
lien perception-production en parole. La thèse sera codirigée par A. Basirat
(https://scalab.univ-lille.fr) et J. Diard (https://lpnc.univ-grenoble-alpes.fr/). Les
informations concernant le projet, les compétences attendues et la modalité de
candidature sont disponibles à l’adresse ci-dessous :

https://emploi.cnrs.fr/Offres/Doctorant/UMR9193-ANABAS-001/Default.aspx

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Job Offer: PhD Causal Machine Learning Applied to NLP and the Study of Large Language
Models.
Starting date: November 1st, 2023 (flexible)
Application deadline: From now until the position is filled
Interviews (tentative):  Beginning of June and latter if the position is still open
Salary: ~2000€ gross/month (social security included)
Mission: research oriented (teaching possible but not mandatory)
Place of work (no remote): Laboratoire d'Informatique de Grenoble, CNRS, Grenoble, France

Keywords: natural language processing, causal machine learning, interpretability,
analysis, robustness, large language models, controllability

Description:
Natural language processing (NLP) has undergone a paradigm shift in recent years, owing
to the remarkable breakthroughs achieved by large language models (LLMs). Despite being
purely 'correlation machines' [CorrelationMachine], these models have completely altered
the landscape of NLP by demonstrating impressive results in language modeling,
translation, and summarization. Nonetheless, the use of LLMs has also surfaced crucial
questions regarding their reliability and transparency. As a result, there is now an
urgent need to gain a deeper understanding of the mechanisms governing the behavior of
LLMs, to interpret their decisions and outcomes in principled and scientifically grounded
ways.

A promising direction to carry out such analysis comes from the fields of causal analysis
and causal inference [CausalAbstraction]. Examining the causal relationships between the
inputs, outputs, and hidden states of LLMs, can help to build scientific theories about
the behavior of these complex systems. Furthermore, causal inference methods can help
uncover underlying causal mechanisms behind the complex computations of LLMs, giving hope
to better interpret their decisions and understand their limitations [Rome].

Thus, the use of causal analysis in the study of LLMs is a promising research direction
to gain deeper insights into the workings of these models.
As a Ph.D student working on this project, you will be expected to develop a strong
understanding of the principles of causal inference and their application to machine
learning, see for example the invariant language model framework [InvariantLM]. You will
have the opportunity to work on cutting-edge research projects in NLP, contributing to
the development of more reliable and interpretable LLMs. It is important to note that the
Ph.D. research project should be aligned with your interests and expertise. Therefore,
the precise direction of the research can and will be influenced by the personal taste
and research goals of the students. It is encouraged that you bring your unique
perspective and ideas to the table.

SKILLS
Master degree in Natural Language Processing, computer science or data science.
Mastering Python programming and deep learning frameworks.
Experience in causal inference or working with LLMs
Very good communication skills in English, (French not needed).

SCIENTIFIC ENVIRONMENT
The thesis will be conducted within the Getalp teams of the LIG laboratory
(https://lig-getalp.imag.fr/). The GETALP team has a strong expertise and track record in
Natural Language Processing. The recruited person will be welcomed within the team which
offer a stimulating, multinational and pleasant working environment.
The means to carry out the PhD will be provided both in terms of missions in France and
abroad and in terms of equipment. The candidate will have access to the cluster of GPUs
of both the LIG. Furthermore, access to the National supercomputer Jean-Zay will enable
to run large scale experiments.
The Ph.D. position will be co-supervised by Maxime Peyrard and François Portet.
Additionally, the Ph.D. student will also be working with external academic collaborators
at EPFL and Idiap (e.g., Robert West and Damien Teney)

INSTRUCTIONS FOR APPLYING
Applications must contain: CV + letter/message of motivation + master notes + be ready to
provide letter(s) of recommendation; and be addressed to Maxime Peyrard
(maxime.peyrard@epfl.ch) and François Portet (francois.Portet@imag.fr)


[InvariantLM] Peyrard, Maxime and Ghotra, Sarvjeet and Josifoski, Martin and Agarwal,
Vidhan and Patra, Barun and Carignan, Dean and Kiciman, Emre and Tiwary, Saurabh and
West, Robert, 'Invariant Language Modeling' Conference on Empirical Methods in Natural
Language Processing (2022): 5728–5743

[CorrelationMachine] Feder, Amir and Keith, Katherine A. and Manzoor, Emaad and Pryzant,
Reid and Sridhar, Dhanya and Wood-Doughty, Zach and Eisenstein, Jacob and Grimmer, Justin
and Reichart, Roi and Roberts, Margaret E. and Stewart, Brandon M. and Veitch, Victor and
Yang, Diyi, 'Causal Inference in Natural Language Processing: Estimation, Prediction,
Interpretation and Beyond' Transactions of the Association for Computational Linguistics
(2022), 10:1138–1158.

[CausalAbstraction] Geiger, Atticus and Wu, Zhengxuan and Lu, Hanson and Rozner, Josh and
Kreiss, Elisa and Icard, Thomas and Goodman, Noah and Potts, Christopher, 'Inducing
Causal Structure for Interpretable Neural Networks' Proceedings of Machine Learning
Research (2022): 7324-7338.

[Rome] Meng, Kevin, et al. 'Locating and Editing Factual Associations in GPT.' Advances
in Neural Information Processing Systems 35 (2022): 17359-17372.

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The application deadline is ** June 2, 2023 **

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In the framework of the PEPR Santé numérique “Autonom-Health” project (Health, behaviors and autonomous digital technologies), the speech and language research group at the Computer Science Lab in Bordeaux, France (LaBRI) and the LORIA (Nancy, France) are looking for candidates for a fully funded PhD position (36 months).  

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Open faculty position at KU Leuven, Belgium: junior professor in Synergistic Processing
of Multisensory Data for Audio-Visual Understanding

KU Leuven's Faculty of Engineering Science has an open position for a junior professor
(tenure track) in the area of audiovisual understanding. The successful candidate will
conduct research on synergetic processing of multisensory data for audio-visual
understanding, teach courses in the Master of Engineering Science and supervise students
in the Master and PhD programs. The candidate will be embedded in the PSI research
division of the Department of Electrical Engineering. More information is available at
https://www.kuleuven.be/personeel/jobsite/jobs/60193566?hl=en&lang=en . The deadline for
applications is September 29, 2023.

KU Leuven is committed to creating a diverse environment. It explicitly encourages
candidates from groups that are currently underrepresented at the university to submit
their applications.

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PhD in ML/NLP – Fairness and self-supervised learning for speech processing
Starting date: October 1st, 2023 (flexible)
Application deadline: June 9th, 2023
Interviews (tentative): June 14th, 2023

Salary: ~2000€ gross/month (social security included)

Mission: research oriented (teaching possible but not mandatory)

Keywords: speech processing, fairness, bias, self-supervised learning, evaluation metrics 

CONTEXT

This thesis is in the context of the ANR project E-SSL (Efficient Self-Supervised Learning for Inclusive and Innovative Speech Technologies). Self-supervised learning (SSL) has recently emerged as one of the most promising artificial intelligence (AI) methods as it becomes now feasible to take advantage of the colossal amounts of existing unlabeled data to significantly improve the performances of various speech processing tasks.

PROJECT OBJECTIVES

Speech technologies are widely used in our daily life and are expanding the scope of our action, with decision-making systems, including in critical areas such as health or legal aspects. In these societal applications, the question of the use of these tools raises the issue of the possible discrimination of people according to criteria for which society requires equal treatment, such as gender, origin, religion or disability...  Recently, the machine learning community has been confronted with the need to work on the possible biases of algorithms, and many works have shown that the search for the best performance is not the only goal to pursue [1]. For instance, recent evaluations of ASR systems have shown that performances can vary according to the gender but these variations depend both on  data used for learning and on models [2]. Therefore such systems are increasingly scrutinized for being biased while trustworthy speech technologies definitely represents a crucial expectation.

 Both the question of bias and the concept of fairness have now become important aspects of AI, and we now have to find the right threshold between accuracy and the measure of fairness. Unfortunately, these notions of fairness and bias are challenging to define and their
 meanings can greatly differ [3].

 The goals of this PhD position are threefold:

- First make a survey on the many definitions of robustness, fairness and bias with the aim of coming up with definitions and metrics fit for speech SSL models

- Then gather speech datasets with high amount of well-described metadata

- Setup an evaluation protocol for SSL models and analyzing the results.

SKILLS

• Master 2 in Natural Language Processing, Speech Processing, computer science or data science.

• Good mastering of Python programming and deep learning framework.

• Previous experience in bias in machine learning would be a plus

• Very good communication skills in English

• Good command of French would be a plus but is not mandatory 

SCIENTIFIC ENVIRONMENT

The PhD position will be co-supervised by Alexandre Allauzen (Dauphine Université PSL, Paris) and Solange Rossato and François Portet (Université Grenoble Alpes). Joint meetings are planned on a regular basis and the student is expected to spend time in both places. Moreover, two other PhD positions are open in this project.  The students, along with the partners will closely collaborate. For instance, specific SSL models along with evaluation criteria will be developed by the other PhD students. Moreover, the PhD student will collaborate with several team members involved in the project in particular the two other PhD candidates who will be recruited  and the partners from LIA, LIG and Dauphine Université PSL, Paris. The means to carry out the PhD will be provided both in terms of missions in France and abroad and in terms of equipment. The candidate will have access to the cluster of GPUs of both the LIG and Dauphine Université PSL. Furthermore, access to the National supercomputer Jean-Zay will enable to run large scale experiments.

INSTRUCTIONS FOR APPLYING

Applications must contain: CV + letter/message of motivation + master notes + be ready to provide letter(s) of recommendation; and be addressed to Alexandre Allauzen (alexandre.allauzen@espci.psl.eu), Solange Rossato (Solange.Rossato@imag.fr) and François Portet (francois.Portet@imag.fr). We celebrate diversity and are committed to creating an inclusive environment for all employees.

REFERENCES:

[1] Mengesha, Z., Heldreth, C., Lahav, M., Sublewski, J. & Tuennerman, E. “I don’t Think These Devices are Very Culturally Sensitive.”—Impact of Automated Speech Recognition Errors on African Americans. Frontiers in Artificial Intelligence 4. issn: 2624-8212. https://www.frontiersin.org/article/10.3389/frai.2021.725911 (2021).

[2] Garnerin, M., Rossato, S. & Besacier, L. Investigating the Impact  of Gender Representation in ASR Training Data: a Case Study on Librispeech in Proceedings of the 3rd Workshop on Gender Bias in Natural Language Processing (2021), 86–92.
[3] Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K. & Galstyan, A. A Survey on Bias and Fairness in Machine Learning.  ACMComput. Surv. 54. issn: 0360-0300. https://doi.org/10.1145/3457607 (July 2021).

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In the framework of the European FETPROACT « Fvllmonti » project and the PEPR Santé numérique “Autonom-Health” project, the speech and language research group at the Computer Science Lab in Bordeaux, France (LaBRI) is looking for candidates for a 24-months post-doctoral position. 

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ELDA (Evaluations and Language resources Disctribution Agency) looks for full/part time transcriptors for transcription of phone calls in the financial domain.

Location: ELDA (Paris-France)

Latest starting date: July 2023

Languages and mission details

• German - 21h of speech to be transcribed + phonetisation task;
• Spanish - 1h of speech to be transcribed;
• Italian - 1h of speech to be transcribed;
• Japanese - 21h of speech to transcribe + phonetisation task;
• Polish - number of hours vary as it is still being tested.

Profile

• Native expertise in the selected language with a very good level of spelling and grammar;
• Good knowledge of French and/or English;
• Good computer skills;
• Ability to integrate and scrupulously follow transcription rules.

Salary and duration

• Starting from SMIC depending on skills;
• Approximately 3 months (FT for the longer assignments).

Application

• Send your CV to <lucille@elda.org> ou <gabriele@elda.org>;
• Include [Transcription *language*] in the object field.

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DRhyaDS

A new framework for understanding the Dynamic Rhythms and Decoding of Speech

Job Title - Postdoctoral Researcher

Disciplines and Areas of Research - Speech science, Psycholinguistics, Psychoacoustics

Contract Duration - 1 Year

Research Overview: The DRhyaDS project aims to develop a new framework for understanding the dynamic rhythms and decoding of speech. It focuses on exploring the temporal properties of speech and their contribution to speech perception. The project challenges the conventional view that speech rhythm perception relies on a one-to-one association between specific modulation frequencies in the speech signal and linguistic units. One of the key objectives of the project is to investigate the impact of language-specific temporal characteristics on speech dynamics. The project team will analyze two corpora of semi-spontaneous speech data from French and German, representing syllable-timed and stress-timed languages, respectively. Various acoustic analyses will be conducted on these speech corpora to explore the variability of slow temporal modulations in speech at an individual level. This comprehensive acoustic exploration will involve extracting and analyzing prosody, spectral properties, temporal dynamics, and rhythmic patterns. By examining these acoustic parameters, the project aims to uncover intricate details about the structure and variation of speech signals across languages and speakers, contributing to a more nuanced understanding of the dynamic nature of spoken language and its role in human communication. Environment: The selected candidate will be an integral part of an international research team and will work in a collaborative and stimulating lab environment. The project brings together a FrancoGerman team of experts in linguistics, psychoacoustics and cognitive neuroscience, led by Dr. Léo Varnet (CNRS, ENS Paris) and Dr. Alessandro Tavano (Max Planck Institute, Goethe University Frankfurt). The successful candidate will work under the supervision of Dr Léo Varnet, at the Laboratoire des Systèmes Perceptifs (ENS Paris).

Job description: This is a one-year postdoctoral contract position, offering a net salary in accordance with French legislation (~2500€/month + social and medical benefits). Women and minorities are strongly encouraged to apply. The successful candidate will participate in research activities, collaborate with team members, and contribute to scientific publications and communications. Additionally, they will have the autonomy to suggest and implement their own analysis techniques and approaches. Their responsibilities will include: - Taking a lead role in collecting a comprehensive corpus of French speech data, adhering to a rigorous data collection protocol - Collaborating closely with the German team to leverage the existing German speech corpus for comparative analysis and cross-linguistic investigations - Conducting in-depth acoustic analysis of the corpora, employing advanced techniques to investigate the variability and dynamics of slow temporal modulations in speech - Actively participating in team meetings, workshops, and conferences to present research progress, exchange ideas, and contribute to the intellectual growth of the project - Engaging in science outreach activities to promote the project's research outcomes and facilitate public understanding of speech perception and language processing.

Qualifications: - A recently obtained PhD in a relevant field (e.g., linguistics, psychology, neuroscience, computational sciences) - Strong expertise in linguistics, speech perception, acoustic analysis, and statistical methods - Proficiency in programming languages commonly used in speech research. Knowledge of MATLAB would be particularly valuable for data processing and analysis within the project. - Strong written and verbal communication skills in English. Candidates with proficiency in French and/or German language skills would be particularly appreciated, as it would enable a deeper understanding of the linguistic characteristics of the respective corpora.

Application process To apply for this position, please submit a CV and a cover letter (in French or English) along with the names and contact information of 2 referees to Léo Varnet (leo.varnet@cnrs.fr). The application deadline is 31th July 2023. Interviews will be conducted in September. The ideal start date is October-November 2023, with some flexibility allowed. Feel free to get in touch informally to discuss this position

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Inria is opening a fully funded PhD position on multimodal speech
anonymization. For details and to apply, see:
https://jobs.inria.fr/public/classic/en/offres/2023-06410

Applications will be reviewed on a continuous basis until July 2.

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Call for postdoc applications in Natural Language Processing for the automatic detection of gender stereotypes in the French media (Grenoble Alps University, France)

Starting date:                flexible,  November 30, 2023, at the latest

Duration:                       full-time position for 12 months

Salary:                         according to experience (up to 4142€/ month)

Application Deadline: Open until filled

Location:               The position will be based in Grenoble, France. This is not a remote work.

Keywords:             natural language processing, gender stereotypes                                 bias, corpus analysis, language models, transfer                                 learning, deep learning

*Context* The University of Grenoble Alps (UGA) has an open position for a highly motivated postdoc researcher to joint the multidisciplinary GenderedNews project. Natural Language Processing models trained on large amount of on-line content, have quickly opened new perspectives to process on-line large amount of on-line content for measuring gender bias in a daily basis (see our project https://gendered-news.imag.fr/ ). Regarding research on stereotypes, most recent works have studied Language Models (LM) from a stereotype perspective by providing specific corpora such as StereoSet (Nadeem et al., 2020) or CrowS-Pairs (Nangia et al. 2020). However, these studies are focusing on the quantifying of bias in the LM predictions rather than bias in the original data (Choenni et al., 2021). Furthermore, most of these studies ignore named entities (Deshpande et al., 2022) which account for an important part of the referents and speakers in news. In this project, we intend to build corpora, methods and NLP tools to qualify the differences between the language used to describe groups of people in French news.

*Main Tasks*

The successful postdoc will be responsible for day-to-day running of the research project, under the supervision of François Portet (Prof UGA at LIG) and Gilles Bastin (prof UGA at PACTE). Regular meetings will take place every two weeks.

- Defining the dimensions of stereotypes to be investigated and the possible metrics that can be processed from a machine learning perspective.

- Exploring, managing and curating news corpora in French for stereotypes investigation, with a view to making them widely available to the community to favor reproducible research and comparison.

- Studying and developing new computational models to process large number of texts to reveal stereotype bias in news. Make use of pretrained models for the task.

- Evaluate the methods on curated focused corpus and apply it to the unseen real longitudinal corpus and analyze the results with the team.

- Preparing articles for submission to peer-reviewed conferences and journals.

- Organizing progress meetings and liaising between members of the team. 

The hired person will interact with PhD students, interns and researchers being part of the GenderedNews project. According to his/her background his/her own interests and in accordance with the project's objective, the hired person will have the possibility to orient the research in different directions.

*Scientific Environment*

The recruited person will be hosted within the GETALP teams of the LIG laboratory (https://lig-getalp.imag.fr/), which offers a dynamic, international, and stimulating environment for conducting high-level multidisciplinary research. The person will have access to large datasets of French news, GPU servers, to support for missions as well as to the scientific activities of the labs. The team is housed in a modern building (IMAG) located in a 175-hectare landscaped campus that was ranked as the eighth most beautiful campus in Europe by the Times Higher Education magazine in 2018.

The person will also closely work with Gilles Bastin (PACTE, a Sociology lab in Grenoble) and Ange Richard (PhD at LIG and PACTE). The project also includes an informal collaboration with 'Prenons la une' (https://prenonslaune.fr/) a journalists’ association which promotes a fair representation of women in the media.

*Requirements*

The candidate must have a PhD degree in Natural Language Processing or computer science or in the process of acquiring it. The successful candidate should have

-  Good knowledge of Natural Language Processing -  Experience in corpus collection/formatting and manipulation. -  Good programming skills in Python -  Publication record in a close field of research -  Willing to work in multidisciplinary and international teams -  Good communication skills -  Good mastering of French is required

*Instructions for applying*

Applications will be considered on the fly and must be addressed to François Portet (Francois.Portet@imag.fr). It is therefore advisable to apply as soon as possible. The application file should contain

-   Curriculum vitae -   References for potential letter(s) of recommendation -   One-page summary of research background and interests for the position -   Publications demonstrating expertise in the aforementioned areas -   Pre-defense reports and defense minutes; or summary of the thesis with the date of defense for those currently in doctoral studies

*References*

Deshpande et al. (2022). StereoKG: Data-Driven Knowledge Graph Construction for Cultural Knowledge and Stereotypes. arXiv preprint arXiv:2205.14036.

Choenni et al. (2021). Stepmothers are mean and academics are pretentious: What do pretrained language models learn about you? arXiv preprint arXiv:2109.10052.

Nadeem et al. (2020) StereoSet: Measuring stereotypical bias in pretrained language models. ArXiv.

Nangia et al. (2020) CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models. In EMNLP2020.

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the new Postdoc-Kolleg 'Education and AI in the 21st century.

Technology-enabled innovations in subject-specific teaching

settings (PostdocTEIFUN)' of the Tübingen School of Education (TüSE)

and Professional School of Education Stuttgart-Ludwigsburg (PSE) will

start in 2024.

It is offering six Post-doc positions funded for six years (100% TVL

E14) to conduct interdisciplinary research in the field of education

and AI.

The official announcement can be found here:

https://uni-tuebingen.de/universitaet/stellenangebote/newsfullview-stellenangebote/article/6-akademische-ratsstellen-m-w-d-e-14-tv-l-100/

Among the various potential research fields, the following could be of

interest here:

'Development of didactically informed Intelligent Language Tutoring

approaches targeting spoken language learning for the English

classroom. Potential directions include but are not limited to the

realization of perceptual training, input enhancement, automatic

corrective feedback, or prosodic complexity analysis.'

Interested? Please contact us at:

Sabine Zerbian, sabine.zerbian@ifla.uni-stuttgart.de

Detmar Meurers, detmar.meurers@uni-tuebingen.de

Note that there is a tight deadline for applications: 30.06.2023

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In a joint research project *VidQA*, our collaboration partner from University of Applied Sciences (Prof. Christian Wartena, HsH Hochschule Hannover) offers a full position (three years, as soon as possible) for a PhD student:

*VidQA* is a joint research project of the Institute for Applied Data Science Hannover (DATA|H) of the HsH, the Research Center L3S of the Leibniz University and the TIB – Leibniz Information Centre for Science and Technology. The goal of the project is the development and evaluation of new methods for semi-automatic generation of questions and answers for learning videos. Here, we pursue several research questions, such as, among others, the aspect of multimodality of video-based learning media, the generation of distractors ('wrong answers') for multiple-choice questions, and the automatic evaluation of answers for open-ended question formats.

*What you can expect*:

-  Develop and implement procedures for generating (multiple choice) questions, answers, and distractors.

-  Development and implementation of procedures for scoring free text answers

-  Collaboration in the development and evaluation of a system for examing comprehension of learning videos

-  Publication of research and development results at conferences and in professional journals

-  Participation in the organization the project

*Requirements*

Research Field: Computer science

Education Level: Master Degree or equivalent

Skills/Qualifications

-  Master's degree (or equivalent) in computer science or computational linguistics

-  In-depth knowledge in the field of artificial intelligence and machine learning

-  Proven knowledge in Natural Language Processing (NLP)

-  Gender and diversity skills

Languages:     ENGLISH

Level:     Excellent

Languages:    GERMAN

Level:     Good

Website for additional job details: https://karriere.hs-hannover.de/bewerbung/beschreibung-900000104-10057.html

Where to apply: https://karriere.hs-hannover.de/bewerbung/beschreibung-900000104-10057.html

*First Contact*

************************************

Prof. Dr. Christian Wartena

University of Applied Sciences (HsH Hochschule Hannover)

Institute for Applied Data Science Hannover (DATA|H)

E-Mail: christian.wartena@hs-hannover.de

Postal address

City:    Hannover

Website:     https://www.hs-hannover.de/forschung/forschungsaktivitaeten/forschungscluster/smart-data-analytics

Street:     Expo Plaza 12

Postal Code:     30539

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Pour plus d'informations voir :
https://emploi.cnrs.fr/Offres/Doctorant/UMR7020-RICMAR-001/Default.aspx

Pour candidater remplissez le formulaire suivant : https://forms.gle/DdaV8BhN3E4DuXnA8

La date de clôture à candidatures est le 10 juillet 2023.

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Ingénieur chef de projet ressources et technologies linguistiques
 
Centre Inria : CRI Nancy - Grand Est 

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Call for postdoc applications in Natural Language Processing for the automatic detection of gender stereotypes in the French media (Grenoble Alps University, France)

Starting date:                flexible,  November 30, 2023, at the latest

Duration:                       full-time position for 12 months

Salary:                         according to experience (up to 4142€/ month)

Application Deadline: Open until filled

Location:               The position will be based in Grenoble, France. This is not a remote work.

Keywords:             natural language processing, gender stereotypes                                 bias, corpus analysis, language models, transfer                                 learning, deep learning

*Context* The University of Grenoble Alps (UGA) has an open position for a highly motivated postdoc researcher to joint the multidisciplinary GenderedNews project. Natural Language Processing models trained on large amount of on-line content, have quickly opened new perspectives to process on-line large amount of on-line content for measuring gender bias in a daily basis (see our project https://gendered-news.imag.fr/ ). Regarding research on stereotypes, most recent works have studied Language Models (LM) from a stereotype perspective by providing specific corpora such as StereoSet (Nadeem et al., 2020) or CrowS-Pairs (Nangia et al. 2020). However, these studies are focusing on the quantifying of bias in the LM predictions rather than bias in the original data (Choenni et al., 2021). Furthermore, most of these studies ignore named entities (Deshpande et al., 2022) which account for an important part of the referents and speakers in news. In this project, we intend to build corpora, methods and NLP tools to qualify the differences between the language used to describe groups of people in French news.

*Main Tasks*

The successful postdoc will be responsible for day-to-day running of the research project, under the supervision of François Portet (Prof UGA at LIG) and Gilles Bastin (prof UGA at PACTE). Regular meetings will take place every two weeks.

- Defining the dimensions of stereotypes to be investigated and the possible metrics that can be processed from a machine learning perspective.

- Exploring, managing and curating news corpora in French for stereotypes investigation, with a view to making them widely available to the community to favor reproducible research and comparison.

- Studying and developing new computational models to process large number of texts to reveal stereotype bias in news. Make use of pretrained models for the task.

- Evaluate the methods on curated focused corpus and apply it to the unseen real longitudinal corpus and analyze the results with the team.

- Preparing articles for submission to peer-reviewed conferences and journals.

- Organizing progress meetings and liaising between members of the team. 

The hired person will interact with PhD students, interns and researchers being part of the GenderedNews project. According to his/her background his/her own interests and in accordance with the project's objective, the hired person will have the possibility to orient the research in different directions.

*Scientific Environment*

The recruited person will be hosted within the GETALP teams of the LIG laboratory (https://lig-getalp.imag.fr/), which offers a dynamic, international, and stimulating environment for conducting high-level multidisciplinary research. The person will have access to large datasets of French news, GPU servers, to support for missions as well as to the scientific activities of the labs. The team is housed in a modern building (IMAG) located in a 175-hectare landscaped campus that was ranked as the eighth most beautiful campus in Europe by the Times Higher Education magazine in 2018.

The person will also closely work with Gilles Bastin (PACTE, a Sociology lab in Grenoble) and Ange Richard (PhD at LIG and PACTE). The project also includes an informal collaboration with 'Prenons la une' (https://prenonslaune.fr/) a journalists’ association which promotes a fair representation of women in the media.

*Requirements*

The candidate must have a PhD degree in Natural Language Processing or computer science or in the process of acquiring it. The successful candidate should have

-  Good knowledge of Natural Language Processing -  Experience in corpus collection/formatting and manipulation. -  Good programming skills in Python -  Publication record in a close field of research -  Willing to work in multidisciplinary and international teams -  Good communication skills -  Good mastering of French is required

*Instructions for applying*

Applications will be considered on the fly and must be addressed to François Portet (Francois.Portet@imag.fr). It is therefore advisable to apply as soon as possible. The application file should contain

-   Curriculum vitae -   References for potential letter(s) of recommendation -   One-page summary of research background and interests for the position -   Publications demonstrating expertise in the aforementioned areas -   Pre-defense reports and defense minutes; or summary of the thesis with the date of defense for those currently in doctoral studies

*References*

Deshpande et al. (2022). StereoKG: Data-Driven Knowledge Graph Construction for Cultural Knowledge and Stereotypes. arXiv preprint arXiv:2205.14036.

Choenni et al. (2021). Stepmothers are mean and academics are pretentious: What do pretrained language models learn about you? arXiv preprint arXiv:2109.10052.

Nadeem et al. (2020) StereoSet: Measuring stereotypical bias in pretrained language models. ArXiv.

Nangia et al. (2020) CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models. In EMNLP2020.

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The Evaluations and Language resources Distribution Agency (ELDA), a company specialized in Human Language Technologies within an international context is currently seeking to fill an immediate vacancy for the permanent position: Project Manager - Intellectual Property, Personal Data Protection for AI and Language Technologies.

Job description

Under the CEO’s supervision, the Project Manager will handle legal issues related to the compilation, use and distribution of language datasets in a European and international environment. This yields excellent opportunities for creative, and motivated candidates wishing to participate actively in the Language Engineering field.

Their main tasks will consist of:

• Analysing the legal status of language datasets and language models;
• Implementing data protection requirements in the processing and distribution of language data;
• Analysing data collection legal issues;
• Drafting and negotiating distribution contracts for language datasets to be added to an online catalogue;
• Implementing evaluation procedures for IPR clearance of digital data;
• Assessing ethical practices within our activities.

The position is based in Paris.

Salary: Commensurate with qualifications and experience (between 40-60K€).

Other benefits: complementary health insurance and meal vouchers.

Required profile:

• PhD (or Master’s degree + at least 3 years’ experience) in IT Law, with good understanding of intellectual property and data protection;
• Fluent English, with advanced writing and analytical skills;
• Experience implementing data protection regulations;
• Knowledge of the European digital regulatory environment (eg. Digital Services Act, Digital Market Act, Data Act, Digital Governance Act, Open Data Directive, AI Act);
• Familiar with public licensing schemes (CC, GPL, etc.); 
• Involvement in European or international projects related to IPR and other legal aspects;
• Dynamic, communicative, flexible and capable of working independently as well as in a team;
• EU citizen, or residence permit enabling to work in France.

About

ELDA is an SME established in 1995 to promote the development and exploitation of Language Resources (LRs). Language Resources include all data necessary for language engineering, such as monolingual and multilingual lexica, text corpora, speech databases and terminology. ELDA’s role is to produce LRs, to collect and to validate them and, foremost, make them available to users in compliance with applicable regulations and ethical requirements.

For further information about ELDA, visit: http://www.elda.org  

Applicants should email a cover letter addressing the points listed above together with a curriculum vitae to:

ELDA
9 rue des Cordelières
75013 Paris
FRANCE
Email: job@elda.org

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The Signal Processing and Speech Communication Laboratory (https://www.spsc.tugraz.at) of
Graz University of Technology (TU Graz) is looking for

    2 Research and Teaching Associates
            – PhD Positions –
    in Signal Processing and Speech Communication

with appointments planned for November 2023.

Both associates are expected to perform excellent research towards a PhD degree (often in cooperation with international partners) under the guidance of professors Gernot Kubin and Barbara Schuppler. Furthermore, the associates will co-advise Bachelor’s and Master’s student projects and develop and teach laboratory and problem classes on various aspects of signal processing. Fluency in English is a must, knowledge of German is an asset. A strong background in signal processing and/or speech communication as well as an excellent Master’s degree in Electrical Engineering, Information Engineering, or similar are required.

Entry-level gross yearly salaries are about EUR 45.900,- for 40 hrs per week and initial contract durations may span up to 4 years.

The Signal Processing and Speech Communication Laboratory was the main organizer of INTERSPEECH 2019 in Graz (https://www.interspeech2019.org) and takes the lead in building a Graduate School of Excellence in European Speech and Language Technologies together with seven partners of the Unite! University Alliance (https://www.unite-university.eu). TU Graz is ranked #2 of all universities in the German speaking countries (https://www.umultirank.org).

Graz (https://www.graztourismus.at/en) is the second largest city of Austria located in the south-eastern province of Styria at the cross-roads of major continental European cultures. It enjoys a vibrant student life with eight universities and excellent leisure and sports opportunities in the larger Alps-Adriatic region. UNESCO has included the historic centre of Graz in its World Heritage List and Graz has been a Cultural Capital of Europe.

For further information, please contact the two advisors
Gernot Kubin at gernot.kubin@tugraz.at  and Barbara Schuppler at b.schuppler@tugraz.at.

Applications are due by September 27, 2023, and must be submitted electronically at
https://jobs.tugraz.at/en/jobs/b645ee47-c3aa-712a-29b3-64d61edea5e6.

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The School of Electrical Engineering and Computer Science (EECS) at the KTH Royal Institute of Technology announces a fully funded Ph.D position in machine learning for conversational AI at the division of Speech, Music, and Hearing (TMH).

ABOUT KTH
KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities, as well as a key center of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as in architecture, industrial management, urban planning, history and philosophy.

The doctoral position is offered by the division of Speech, Music and Hearing (https://www.speech.kth.se/). It is an internationally prominent research group within speech technology and related areas with a heritage that ranges back to the early 50s. It was one of the first research groups of its kind, and is likely the oldest that is still active. The group is in the forefront of fundamental research in areas such as speech analysis, analysis of human communicative behaviours, audiovisual synthesis and generation, speech perception and understanding, and multimodal dialogue systems.


PROJECT DESCRIPTION
The task of the candidate is to develop and evaluate the usefulness of a generative AI and expressive
speech synthesis in Augmentative Communication Technology for individuals with communication disabilities. As the AI voice system is designed for users who input text using gaze trackers the project also involves using Large Language models to speed up the text input given the previous context.
The system will leverage the KTH spontaneous TTS (http://www.speech.kth.se/tts-demos/)

Supervision: The doctoral student will be supervised by
Joakim Gustafson (https://www.speech.kth.se/~jocke/)
and
Éva Székely (https://www.linkedin.com/in/eva-szekely-48459528a/)

The starting date for the positions is flexible, but as soon as possible.

What we offer
- Workplace that focus on working conditions, gender equality, diversity, study environment
- A monthly salary of around 3.000 EUR, and benefits such as 6 weeks paid vacation, health insurance, paid parental leave and occupational pensions.

QUALIFICATIONS
The candidate must have a degree in Computer Science or related fields.  In order to succeed as doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to work both independently and to collaborate with others. Other important traits are openness toward interdisciplinary research, creativity and a structured approach. Good command of spoken and written English is required. Expertise in machine learning/deep learning and good programming skills are strongly desirable. Experience and interest in areas like speech technology, signal processing, natural language processing, linguistics, perception is also considered as asset. After the qualification requirements, great emphasis will be placed on personal qualities and personal suitability.

HOW TO APPLY

The application should include:
1. Curriculum vitae.
2. Transcripts from University/College.
3. Brief description of why the applicant wishes to become a doctoral student.


More information here:
https://www.speech.kth.se/vacancies/


The application documents should be uploaded using the KTH's recruitment system.
 https://kth.varbi.com/en/what:job/jobID:655390/type:job/where:4/apply:1

The application deadline is ** October 10, 2023 **

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