(2020-03-03) 15 early-stage researcher positions available within the COBRA Marie Sklodowska-Curie Innovative Training Network, Berlin, Germany
15 early-stage researcher positions available within the COBRA Marie Sklodowska-Curie Innovative Training Network
A call for applications is open for 15 three-year contracts offered to early-stage researchers (ESRs) wishing to enrol as PhD students in the framework of the Conversational Brains (COBRA) project.
COBRA is a Marie Sklodowska-Curie Innovative Training Network funded by the European Commission within the Horizon 2020 programme. It aims to train ESRs to accurately characterize and model the linguistic, cognitive and brain mechanisms that allow conversation to unfold in both human-human and human-machine interactions.
The network comprises ten academic research centers on language, cognition and the human brain, and four industrial partners in web-based speech technology, conversational agents and social robots, in ten countries.
The partners? combined expertise and high complementarity will allow COBRA to offer ESRs an excellent training programme as well as very strong exposure to the non-academic sector.
Deadline for submission of applications: 31 March 2020
ESR1: Categorization of speech sounds as a collective decision process Recruiter & PhD enrolment at: Aix-Marseille University (France)
ESR2: Brain markers of between-speaker convergence in conversational speech Recruiter: Italian Institute of Technology, Ferrara (Italy), PhD enrolment at: University of Ferrara
ESR3: Does prediction drive neural alignment in conversation? Recruiter & PhD enrolment at: Aix-Marseille University (France)
ESR4: Brain indexes of semantic and pragmatic prediction Recruiter & PhD enrolment at: Freie Universität Berlin (Germany)
ESR5: Communicative alignment at the physiological level Recruiter & PhD enrolment at: Humboldt-Universität zu Berlin / ZAS, Berlin (Germany)
ESR6: Alignment in human-machine spoken interaction Recruiter & PhD enrolment at: The University of Edinburgh (UK)
ESR7: Contribution of discourse markers to alignment in conversation Recruiter & PhD enrolment at: Université catholique de Louvain, Louvain-la-Neuve (Belgium)
ESR8: Discourse units and discourse alignement Recruiter & PhD enrolment at: Université catholique de Louvain, Louvain-la-Neuve (Belgium)
ESR9: Acoustic-phonetic alignment in synthetic speech Recruiter & PhD enrolment: The University of Edinburgh (UK)
ESR10: Phonetic alignment in a non-native language Recruiter: Italian Institute of Technology, Ferrara (Italy), PhD enrolment at: University of Ferrara
ESR11: Conversation coordination and mind-reading Recruiter: IISAS, Bratislava (Slovakia), PhD enrolment at: Slovak University of Technology, Bratislava
ESR12: The influence of alignment Recruiter: IISAS, Bratislava (Slovakia), PhD enrolment at: Slovak University of Technology, Bratislava
ESR13: Parametric dialogue synthesis: from separate speakers to conversational interaction Recruiter: ReadSpeaker, Huis ter Heide (The Netherlands), PhD enrolment at: Helsinki University (Finland)
ESR14: Gender and vocal alignment in speakers and robots Recruiter: Furhat Robotics, Stockholm (Sweden), PhD enrolment at: Aix-Marseille University (France)
ESR15: Endowing robots with high-level conversational skills Recruiter: Furhat Robotics, Stockholm (Sweden), PhD enrolment at: Radboud Univ., Nijmegen (The Netherlands)
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NOTE MY EMAIL ADRESS: fuchs@zas.gwz-berlin.de WILL EXPIRE SOON.
(2020-03-07) Postdoc researcher in deepNN, University of Glasgow, UK (UPDATED)
APPLICATION DEADLINE EXTENDED TO 13 APRIL
The School of Computing Science at the University of Glasgow is looking for an excellent and enthusiastic researcher to join the ESRC-funded international collaborative project 'Using AI-Enhanced Social Robots to Improve Children's Healthcare Experiences.' This is a new 3-year project which aims to investigate how a social robot can help children cope with potentially painful experiences in a healthcare setting. The system developed in the project will be tested through a hospital-based clinical trial at the end of the project.
In Glasgow, we are looking for a researcher with expertise in applying deep neural network models to the automated analysis of multimodal human behaviour, ideally along with experience integrating such systems into an end-to-end interactive system.
You will be working together with Dr. Mary Ellen Foster in the Glasgow Interactive Systems Section (GIST); you will collaborate closely with Dr. Ron Petrick and his team from the Edinburgh Centre for Robotics at Heriot-Watt University, and will also collaborate with medical and social science researchers at several Canadian universities including University of Alberta, University of Toronto, Ryerson University, McMaster University, and Dalhousie University.
GIST provides an ideal ground for academic growth. It is the leader of a recently awarded Centre for Doctoral Training that is providing 50 PhD scholarships in the next five years in the area of socially intelligent artificial intelligence. In addition, its 7 faculty members have accumulated more than 25,000 Scholar citations and have been or are leading large-scale national and European projects (including the ERC Advanced Grant 'Viajero', the Network Plus grant 'Human Data Interaction', the FET-Open project 'Levitate', and the H2020 project MuMMER) for a total of over £20M in the last 10 years.
The post is full time with funding up to 27 months in the first instance.
Please email MaryEllen.Foster@glasgow.ac.uk with any informal enquiries.
It is the University of Glasgow’s mission to foster an inclusive climate, which ensures equality in our working, learning, research and teaching environment.
We strongly endorse the principles of Athena SWAN, including a supportive and flexible working environment, with commitment from all levels of the organisation in promoting gender equality.
(2020-03-25) Faculté des lettres de Sorbonne Université propose au concours plusieurs postes d'ATER
La faculté des lettres de Sorbonne Université propose au concours plusieurs postes d'ATER (profil Intelligence Artificielle pour les Sciences Humaines) au sein de l'UFR de sociologie et d'informatique pour les sciences humaines. 6 permanents et 5 ATER enseignent l'informatique.
(2020-04-02) Fully funded PhD position, Idiap Research Institute, Martigny, Switzerland
There is a fully funded PhD position open at Idiap Research Institute on Low Level Mechanisms of Language Evolution.
Recently, Idiap has had some success in incorporating physiological processes into backpropagation-style neural architectures. This allows the processes to be trained in the context of the larger network whilst giving the network the capability to recognise and reproduce physiological functions in a natural manner.
In this project, we will apply this technique to the human cochlea and its interface with low level neural mechanisms. We are particularly interested in the efferent pathway from the low level neurological system back to the cochlea. This will allow us to investigate the resulting non-linear feedback relationship.
Idiap is located in Martigny in French speaking Switzerland, but functions in English and hosts many nationalities. PhD students are registered at EPFL. All positions offer quite generous salaries. Martigny has a distillery and a micro-brewery and is close to all manner of skiing, hiking and mountain life.
(2020-04-15) Professor (W3) on AI for Language Technologies, Germany
The Institute of Anthropomatics and Robotics within the Division 2 - Informatics, Economics, and Society - is seeking to fill, as soon as possible, the position of a
Professor (W3) on AI for Language Technologies
The research area of the professorship are methods of artificial intelligence, especially machine learning, for the realization of intelligent systems for human-machine interaction and their evaluation in real-world applications. Possible research topics include natural language understanding, spoken language translation, automatic speech recognition, interactive and incremental learning from heterogeneous data, and the extraction of semantics from image, text and speech data. The professorship contributes to the 'Robotics and Cognitive Systems' focus of the KIT Department of Informatics.
In teaching, the professorship contributes to the education of students of the KIT Department of Informatics, among others in the fields of natural language understanding, neural networks, machine learning, and cognitive systems. Participation in undergraduate teaching of basic courses in computer science in the German language is expected, especially in the field of artificial intelligence. A transition period for acquiring German language skills is provided.
Active participation in interACT (International Center for Advanced Communication Technologies) is desired. Experience in the development of innovations in application fields of artificial intelligence, e.g. with industrial cooperation partners, is advantageous.
We are looking for a candidate with outstanding scientific qualifications and an outstanding international reputation in the above-mentioned field of research. Skills in the acquisition of third-party funding and the management of scientific working groups are expected, as well as very good didactic skills both in basic computer science lectures and in in-depth courses on subjects within the research area of the professorship.
Active participation in the academic tasks of the KIT Department of Informatics and in the self-administration of KIT in Division II is expected as well as participation in the KIT Center Information - Systems - Technologies.
According to § 47 of the Baden-Wuerttemberg University Act (Landeshochschulgesetz des Landes Baden-Württemberg), a university degree, teaching aptitude and exceptional competence in scientific work are required.
KIT is an equal opportunity employer. Women are especially encouraged to apply. Applicants with disabilities will be given preferential consideration if equally qualified. The KIT is certified as a family-friendly university and offers part-time employment, leaves of absence, a Dual Career Service and coaching to actively promote work-life-balance.
Applications with the required documents (curriculum vitae, degree certificates as well as a list of publications) and a perspective paper (maximum of three pages) should be sent by e-mail, preferably compiled into a single PDF document, to dekanat@informatik.kit.edu by 03.05.2020. For enquiries regarding this specific position please contact Professor Dr. Tamim Asfour, e-mail: asfour@kit.edu .
(2020-04-24) PROFESSORSHIP (junior/senior) @ KU Leuven, Belgium
PROFESSORSHIP (junior/senior) @ KU Leuven: EMBODIED LEARNING MACHINES Since their beginnings some 50 years ago, computer vision, speech and natural language processing, and robotics have made progress by various forms and levels of the integration of so-called 'model-based' (e.g. system identification) and 'model-free' (e.g. deep learning) approaches.
However, important challenges remain at the system and application level, where sound, vision, touch, force, motion must be integrated, to reach application-driven and system level performance goals. It is still a mostly unsolved scientific and technical question how to integrate synergistically the mentioned progress into the perception and control of an engineered body that is equipped with all of the mentioned sensory modalities.
The ideal candidate has proven expertise in one or more of the above-mentioned disciplines and wants to progress the state-of-the-art in their integration.
(2020-04-22) 3 research associate positions at Heriot-Watt University, Edinburgh, UK
The Interaction Lab at Heriot-Watt University, Edinburgh, seeks to fill 3 research associate positions in Conversational AI and NLP within the following research areas:
Salary range: £26,715 - £30,942 (Grade 6 without PhD degree) or £32,817 - £40,322 (Grade 7 with PhD degree)
The positions are associated with the EPSRC-funded projects 'Designing Conversational Assistants to Reduce Gender Bias' (positions 1&2) and 'AISEC: AI Secure and Explainable by Construction? (position 3), which are both in collaboration with the University of Edinburgh and other academic and industrial partners, including the University of Glasgow, the University of Strathclyde, the Scottish Government, NEC Labs Europe, Huggingface, and the BBC.
For informal enquiries please contact Prof. Verena Rieser <v.t.rieser@hw.ac.uk>. Untitled Document
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(2020-04-20) Fully-funded PhD studentships in Speech and Language Technologies at the University of Sheffield,UK
UKRI Centre for Doctoral Training (CDT) in Speech and Language Technologies (SLT) and their Applications
Department of Computer Science
Faculty of Engineering
University of Sheffield, UK
Fully-funded 4-year PhD studentships for research in Speech and Language Technologies (SLT) and their Applications
** Applications now open for last remaining September 2020 intake places **
Deadline for applications: 31 May 2020.
Speech and Language Technologies (SLTs) are a range of Artificial Intelligence (AI) approaches which allow computer programs or electronic devices to analyse, produce, modify or respond to human texts and speech. SLTs are underpinned by a number of fundamental research fields including natural language processing, speech processing, computational linguistics, mathematics, machine learning, physics, psychology, computer science, and acoustics. SLTs are now established as core scientific/engineering disciplines within AI and have grown into a world-wide multi-billion dollar industry.
Located in the Department of Computer Science, at the University of Sheffield ? a world leading research institution in the SLT field ? the UKRI Centre for Doctoral Training (CDT) in Speech and Language Technologies and their Applications is a vibrant research centre that also provides training in engineering skills, leadership, ethics, innovation, entrepreneurship, and responsibility to society.
Four-year fully-funded studentship covering all fees and an enhanced stipend (£17,000 pa)
Generous personal allowance for research-related travel, conference attendance, specialist equipment, etc.
A full-time PhD with Integrated Postgraduate Diploma (PGDip) incorporating 6 months of foundational SLT training prior to starting your research project
Bespoke cohort-based training programme running over the entire four years providing the necessary skills for academic and industrial leadership in the field.
Supervision from a team of over 20 internationally leading SLT researchers, covering all core areas of modern SLT research, and a broader pool of over 50 academics in cognate disciplines with interests in SLTs and their application
Every PhD project is underpinned by a real-world application, directly supported by one of our industry partners.
A dedicated CDT workspace within a collaborative and inclusive research environment hosted by the Department of Computer Science
Work and live in Sheffield - a cultural centre on the edge of the Peak District National Park which is in the top 10 most affordable UK university cities (WhatUni? 2019).
About you:
We are looking for students from a wide range of backgrounds interested in Speech and Language Technologies.
High-quality (ideally first class) undergraduate or masters (ideally distinction) degree in a relevant discipline. Suitable backgrounds include (but are not limited to) computer science/software engineering; informatics; AI; speech and language processing; mathematics; physics; linguistics; cognitive science; and engineering.
Regardless of background, you must be able to demonstrate strong mathematical aptitude (minimally to A-Level standard or equivalent) and experience of programming.
We particularly encourage applications from groups that are underrepresented in technology.
Candidates must satisfy the UKRI funding eligibility criteria. Students must have settled status in the UK and have been ?ordinarily resident? in the UK for at least 3 years prior to the start of the studentship. Full details of eligibility criteria can be found on our website.
Applying:
Applications are now sought for the September 2020 intake. The deadline is 31 May 2020.
Applications will be reviewed within 6 weeks of the deadline and short-listed applicants will be invited to interview. Interviews will be held in Sheffield or via videoconference.
See our website for full details and guidance on how to apply: https://slt-cdt.ac.uk
By replying to this email or contacting sltcdt-enquiries@sheffield.ac.uk you consent to being contacted by the University of Sheffield in relation to the CDT. You are free to withdraw your permission in writing at any time.
(2020-04-28) Fully-funded PhD in speech synthesis - University of Grenoble-Alps - France
Fully-funded PhD in speech synthesis - University of Grenoble-Alps - France
Expressive audiovisual speech synthesis for an embodied conversational agent
Funding: THERADIA project funded by BPI-France with industrials (SBT, ATOS, Pertimm). Providing full salary for 3 years (2135? gross monthly) and a generous package for travel & other costs
Deadline: applications will be considered on an ongoing basis until the position is filled
Die Duale Hochschule Baden-Württemberg (DHBW) zählt mit ihren derzeit rund 34.000 Studierenden (an 12 Standorten) und 9.000 kooperierenden Unternehmen und sozialen Einrichtungen zu den größten Hochschulen des Landes. Karlsruhe, in der Rheinebene zwischen Pfälzer Bergen, Vogesen und Schwarzwald gelegen, ist eine junge Großstadt im Herzen Europas. Die TechnologieRegion Karlsruhe ist eine der leistungsfähigsten Regionen Europas. Sie zählt zu den führenden Wissenschafts- und High-Tech-Standorten. Derzeit sind an der DHBW Karlsruhe rund 3.200 Studierende in den Fakultäten Wirtschaft und Technik immatrikuliert.
AN DER DHBW KARLSRUHE IST IN DER FAKULTÄT FÜR TECHNIK FOLGENDE STELLE ZUM 01.04.2021 ZU BESETZEN:
Professur für Informatik (m/w/d)
Besoldungsgruppe W2, Kennziffer: KA-5/111
Neben den Voraussetzungen des § 47 LHG sollte der*die Bewerber*in über folgende Qualifikationen verfügen:
Abgeschlossenes Informatikstudium und Promotion
Einschlägige Berufserfahrung im Bereich Informatik
Sehr gute Fachkenntnisse in einem der Studienschwerpunkte der Informatik: Künstliche Intelligenz, IT-Sicherheit oder Internet of Things sowie deren gesellschaftlicher Anwendung
Zu den Aufgaben gehören die Lehre, die angewandte Forschung und die Weiterbildung im Studiengang Informatik. Neben der Begeisterung für die Lehre erwarten wir die Bereitschaft, den Studiengang fachlich und organisatorisch weiter zu entwickeln. Für das vielseitige Tätigkeitsfeld suchen wir eine führungs- und sozialkompetente Persönlichkeit, die ihre Rolle im Umgang mit den Interessenspartnern des Studiengangs kommunikationsstark und verantwortungsvoll wahrnimmt. Es erwartet Sie ein aufgeschlossenes Team, welches wertschätzend kooperiert und den Studiengang gemeinsam weiterentwickelt.
Einstellungsvoraussetzungen Einstellungsvoraussetzungen Vorausgesetzt werden gemäß § 47 LHG ein abgeschlossenes Hochschulstudium, besondere wissenschaftliche Befähigung (in der Regel Promotion), pädagogische Eignung sowie mindestens fünf Jahre berufspraktische Erfahrung, davon mindestens drei Jahre außerhalb des Hochschulbereichs. Der*Die Bewerber*in muss zudem bereit sein, an der wissenschaftlichen Entwicklung, insbesondere durch Forschung und wissenschaftliche Weiterbildung, teilzuhaben. Erwartet wird ein besonderes Maß an Engagement und Kooperationsbereitschaft mit den beteiligten Unternehmen und sozialen Einrichtungen sowie die Bereitschaft zur Gremienarbeit. Eine Mitwirkung in angemessenem Umfang an den übrigen Aufgaben der DHBW Karlsruhe setzen wir voraus.
Die Übernahme in ein Beamtenverhältnis auf Lebenszeit als Professor*in (W2) ist in der Regel nach dreijähriger Bewährung im Beamtenverhältnis auf Probe möglich, falls das Lebensalter bei der Einstellung 47 Jahre, bei Erfüllung besonderer Voraussetzungen 52 Jahre, nicht übersteigt. Die Stellen sind grundsätzlich teilbar. Bei Teilzeit erfolgt die Anstellung im Beschäftigtenverhältnis und wird außertariflich analog der Besoldungsgruppe W2 vergütet.
Bewerbungen von Frauen sind besonders erwünscht. Schwerbehinderte werden bei gleicher fachlicher Eignung vorrangig berücksichtigt (bitte Nachweis beifügen).
Bei Fragen zum Berufungsverfahren können Sie sich an den Dekan als Vorsitzenden der Berufungskommission oder an die Gleichstellungsbeauftragte, Frau Prof. Dr. Karin Schäfer (karin.schaefer@dhbw-karlsruhe.de), wenden.
Bitte richten Sie Ihre Bewerbung online (idealerweise in einer PDF-Datei) bis zum 13.05.2020 unter Angabe der Kennziffer an:
Nous recherchons des candidat.es motivé.s pour une thèse en IA/Interaction vocale sur le thème :
Transformer et renforcer pour l?apprentissage des agents conversationnels vocaux
Le challenge principal que nous souhaitons porter dans la thèse est de permettre une adaptation sur une tâche particulière des capacités d?un modèle neuronal profond de type Transformer pré-entraîné, notamment pour l?élaboration d?un agent conversationnel. Des approches par transfert d?apprentissage ont déjà été initiées mais leurs résultats sont contrastés et doivent être renforcés. Deux axes majeurs sont identifiés pour la thèse : - élaborer des stratégies efficaces en échantillons pour permettre le recours à des apprentissages par renforcement, en particulier dans le cadre de l?apprentissage en continu (continual learning) d?un agent conversationnel ; - augmenter les capacités de telles machines à faire face à des entrées bruitées, telles que des échanges vocaux avec un utilisateur, plus naturels et comprenant de nombreux écarts vis-à-vis de l?écrit ainsi que des erreurs liées à la transcription automatique de parole.
Les approches envisagées reposent sur les paradigmes les plus avancés du Machine Learning (incluant deep learning et reinforcement learning). Le sujet et les conditions de candidature sont détaillés dans le PDF joint.
L'acceptation du candidat sera validée par un concours au sein de l'Ecole Doctorale 536 d'Avignon Université. Les réponses doivent nous parvenir de préférence **avant le 15 mai**.
(2020-04-28) 1 year post-doc/engineer position at LIA, Avignon France
*1 year post-doc/engineer position at LIA, Avignon France, in the Vocal Interaction Group* ================================================================== Multimodal man-robot interface for social spaces
Starting job date (desired): Sept. 2020. ================================================================== ## Work description
###Project Summary
Automation and optimisation of *verbal interactions of a socially-competent robot*, guided by its *multimodal perceptions*
Facing a steady increase in the ageing population and the prevalence of chronic diseases, social robots are promising tools to include in the healthcare system. Yet extant assistive robots are not well suited to such context as their communication abilities cannot handle social spaces (several meters and group of persons) but rather face-to-face individual interactions in quiet environments. In order to overcome these limitations and eventually aiming at natural man-robot interaction, the objectives of the work will be multifold.
First and foremost we intend to leverage the rich information available with audio and visual flows of data coming from humans to extract verbal and non-verbal features. These features will be used to enhance the robot's decision-making ability such that it can smoothly take speech turns and switch from interaction with a group of people to face-to-face dialogue, and back. Secondly online and continual learning of the advanced system will be investigated.
Outcomes of the project will be implemented onto a commercially available social robot (most likely Pepper or ARI) and validated with several in-situ use cases. A large-scale data collection will complement in-situ tests to fuel further researches. To address our overall objectives the candidates should have a good command of deep learning techniques and tools (including reinforcement/imitation learning) and any combination of competencies in NLP / dialogue systems, vision and robotics.
### Requirements
- Master or PhD in Computer Science, Machine Learning, Computational Linguistics, Mathematics, Engineering or related fields - Expertise in NLP / Dialog systems. Strong knowledge of current NLP / Interactive / Speech techniques is expected. Previous experience with dialogue and interaction and/or vision data is a strong plus. Knowledge in vision and/or robotics are plusses. ? Strong programming skills, Python/C++ programmer of DNN models (preferably with pytorch) - Expertise in Unix environments - Good spoken and written command of English is required. *French is optional.* - Good writing skills. For post-doc publications at top venues (e.g., ACL, EMNLP, SigDial, NeurIPS, ICLR etc) are expected.
## Place
Bordered by the left bank of the Rhône Avignon is one of the most beautiful city in Provence, for some time capital of Christendom in the Middle Ages. Its past gives the city its unique atmosphere: dozens of churches and chapels, the ?Palais des Papes? (palace of the popes, the most important gothic palace in Europe), the Saint-Benezet brigde (aka the « pont d?Avignon » of worldwide fame through its commemoration by the song), and the ramparts that still encircle the entire city, ten museums from then ancient times to contemporary art.
Of the nearly 100k inhabitants of the city, about 10 live in the ancient town centre surrounded by its medieval ramparts. Avignon is not only the birthplace of the most prestigious festival of contemporary theatre, European Capital of Culture in 2000, but also the largest city and capital of the département of Vaucluse. The region offers a high quality urban life at a reasonable cost. Additionally, the region of Avignon offers the opportunity to visit numerous monuments and natural beauty sites easily accessible in a very short time (Marseille, Aix, Montpellier, Nice...). Avignon is the ideal destination for discovering Provence.
The position carries no direct teaching load, but if desired, teaching BSc or MSc level courses is a possibility (paid extra hours), as is supervision of student dissertation projects.
Initial employment is 12 months, extension possible. For engineers, shift to a PhD position is possible.
* Statement of research interests that motivates your application * CV, including the list of publications if any * Scans of transcripts and academic degree certificates * MSc/PhD dissertation and/or any other writing samples * Coding samples or links to your contributions to public code repositories, if any * Names, affiliations, and contact details of up to three people who can provide reference letters for you, if any
(2020-05-10)Researcher at GIPSA-Lab Grenoble, France
L'équipe CRISSP (Cognitive Robotics, Interactive Systems & Speech Robotics) du GIPSA-Lab recherche un(e) candidat(e) motivé(e) pour travailler sur la synthèse de parole appliquée à l'interaction face-à-face incarnée. Il(Elle) devra avoir des compétences en apprentissage automatique.
Le travail s'inscrit dans le cadre du projet THERADIA, financé par BPI-France et mené en partenariat avec des laboratoires (EMC, LIG) et des industriels (SBT, ATOS, Pertimm).
Les candidatures seront examinées de manière continue jusqu'à ce que le poste soit pourvu.
If you know of any interested candidates looking for such a position, please share with them. They are welcome to get in touch with me <p.s.cesar@cwi.nl> concerning any questions prior to any formal application process.
(2020-05-12) Fully-funded 4-year PhD studentships for research in Speech and Language Technologies (SLT) and their Applications , UKRI Centre for doctoral training, Sheffield, UK
UKRI Centre for Doctoral Training (CDT) in Speech and Language Technologies (SLT) and their Applications
Department of Computer Science
Faculty of Engineering
University of Sheffield
Fully-funded 4-year PhD studentships for research in Speech and Language Technologies (SLT) and their Applications
** Applications now open for last remaining September 2020 intake places **
Deadline for applications: 31 May 2020.
What makes the SLT CDT different:
Unique Doctor of Philosophy (PhD) with Integrated Postgraduate Diploma (PGDip) in SLT Leadership.
Bespoke cohort-based training programme running over the entire four years providing the necessary skills for academic and industrial leadership in the field, based on elements covering core SLT skills, research software engineering (RSE), ethics, innovation, entrepreneurship, management, and societal responsibility.
The centre is a world-leading hub for training scientists and engineers in SLT ? two core areas within artificial intelligence (AI) which are experiencing unprecedented growth and will continue to do so over the next decade.
Setting that fosters interdisciplinary approaches, innovation and engagement with real world users and awareness of the social and ethical consequences of work in this area.
The benefits:
Four-year fully-funded studentship covering all fees and an enhanced stipend (£17,000 pa)
Generous personal allowance for research-related travel, conference attendance, specialist equipment, etc.
A full-time PhD with integrated PGDip incorporating 6 months of foundational SLT training prior to starting your research project
Supervision from a team of over 20 internationally leading SLT researchers, covering all core areas of modern SLT research, and a broader pool of over 50 academics in cognate disciplines with interests in SLTs and their application
Every PhD project is underpinned by a real-world application, directly supported by one of over 30 industry partners.
A dedicated CDT workspace within a collaborative and inclusive research environment hosted by the Department of Computer Science
Work and live in Sheffield - a cultural centre on the edge of the Peak District National Park which is in the top 10 most affordable UK university cities (WhatUni? 2019).
About you:
We are looking for students from a wide range of backgrounds interested in Speech and Language Technologies.
High-quality (ideally first class) undergraduate or masters (ideally distinction) degree in a relevant discipline. Suitable backgrounds include (but not limited to) computer science, informatics, engineering, linguistics, speech and language processing, mathematics, cognitive science, AI, physics, or a related discipline.
Regardless of background, you must be able to demonstrate strong mathematical aptitude (minimally to A-Level standard or equivalent) and experience of programming.
We particularly encourage applications from groups that are underrepresented in technology.
Candidates must satisfy the UKRI funding eligibility criteria. Students must have settled status in the UK and have been ?ordinarily resident? in the UK for at least 3 years prior to the start of the studentship. Full details of eligibility criteria can be found on our website.
Applying:
Applications are now sought for the September 2020 intake.
We operate a staged admissions process, with application deadlines throughout the year. The final deadline for applications for the remaining places is 31 May 2020.
Applications will be reviewed within 6 weeks of each deadline and short-listed applicants will be invited to interview. Interviews will be held in Sheffield. In some cases, because of the high volume of applications we receive, we may need more time to assess your application. If this is the case, we will let you know if we intend to do this.
See our website for full details and guidance on how to apply: slt-cdt.ac.uk
By replying to this email or contacting sltcdt-enquiries@sheffield.ac.uk you consent to being contacted by the University of Sheffield in relation to the CDT. You are free to withdraw your permission in writing at any time.
At the recently founded *Multimedia Mining and Search Group*, we are searching for a highly motivated person who holds a *PhD degree in Computer Science or a closely related discipline* to join our young team. We offer a full-time position, great place to work, embedding in a great team, flexibility in the choice of research topics, competitive salary, and social security provisions.
If you are interested and have a strong background in recommender systems, information retrieval, multimedia, data analytics, machine learning, user modeling, and/or human-computer interaction, please contact Markus Schedl (markus.schedl@jku.at) and include the following documents:
* CV (including teaching experience) * Publication list * Certificates (including English translations) * Short statement of your research interests
(2020-05-26) Fully funded PhD position in data-driven socially assistive robotics,Uppsala University, Sweden
** Fully funded PhD position in data-driven socially assistive robotics**
Uppsala Social Robotics Lab
Department of Information Technology
Uppsala University, Sweden
Uppsala University is a comprehensive research-intensive university with a strong international standing. Our mission is to pursue top-quality research and education and to interact constructively with society. Our most important assets are all the individuals whose curiosity and dedication make Uppsala University one of Sweden’s most exciting workplaces. Uppsala University has 46.000 students, 7.300 employees and a turnover of SEK 7.3 billion.
The Department of Information Technology holds a leading position in research as well as teaching at all levels. The department has 280 employees, including 120 faculty, 110 PhD students, and 30 research groups. More than 4000 students are enrolled annually.
The Uppsala Social Robotics Lab (https://usr-lab.com) led by Prof. Ginevra Castellano aims to design and develop robots that learn to interact socially with humans and bring benefits to the society we live in, for example in application areas such as education and assistive technology.
We are collecting expressions of interest for an upcoming PhD position in data-driven socially assistive robotics for medical applications within a project funded by Uppsala University’s WoMHeR (Women’s Mental Health during the Reproductive lifespan) Centre, in collaboration with the Department of Neuroscience.
The PhD project will include the development and evaluation of novel machine learning-based methods for robot-assisted diagnosis of women’s depression around childbirth via automatic analysis of multimodal user behaviour in interactive scenarios.
The student will be part of the Uppsala Social Robotics Lab at the Division of Visual Information and Interaction of the Department of Information Technology.
The Uppsala Social Robotics Lab’s focus is on natural interaction with social artefacts such as robots and embodied virtual agents. This domain concerns bringing together multidisciplinary expertise to address new challenges in the area of social robotics, including mutual human-robot co-adaptation, multimodal multiparty natural interaction with social robots, multimodal human affect and social behavior recognition, multimodal expression generation, robot learning from users, behavior personalization, effects of embodiment (physical robot versus embodied virtual agent) and other fundamental aspects of human-robot interaction (HRI). State of the art robots are used, including the Pepper, Nao and Furhat robotic platforms.
The position is for four years.
Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's rules and guidelines http://regler.uu.se/?languageId=1.
How to send expressions of interest:
To express your interest, you should send to Ginevra Castellano (ginevra.castellano@it.uu.se) by the 10th of June a description of yourself, your research interests, reasons for applying for this particular PhD position and past experience (max. 3 pages), a CV, copies of relevant university degrees and transcripts, links to relevant publications and your MSc thesis (or a summary in case the thesis work is ongoing) and other relevant documents. Candidates are encouraged to provide contact information to up to 3 reference persons. We would also like to know your earliest possible date for starting.
Requirements:
Qualifications: The candidates must have an MSc degree in computer science or related areas relevant to the PhD topics. Good programming skills are required and expertise in machine learning appreciated. The PhD position is highly interdisciplinary and requires an understanding and/or interest in psychology and social sciences and willingness to work in an interdisciplinary team.
Working in Sweden:
Sweden is a fantastic place for living and working. Swedes are friendly and speak excellent English. The quality of life is high, with a strong emphasis on outdoor activities. The Swedish working climate emphasizes an open atmosphere, with active discussions involving both junior and senior staff. PhD students are full employees, with competitive salaries, pension provision and five weeks of paid leave per year. Spouses of employees are entitled to work permits. Healthcare is free after a small co-pay and the university subsidizes athletic costs, such as a gym membership. The parental benefits in Sweden are among the best in the world, including extensive parental leave (for both parents), paid time off to care for sick children, and affordable daycare. Upon completion of the PhD degree, students are entitled to permanent residency to find employment within Sweden.
(2020-06-01) Poste de doctorant financé à l'Université de Grenoble Alpes, France
L'Université Grenoble Alpes recrute un?e doctorant?e (3 ans) entièrement financé?e à partir d'octobre 2020 pour contribuer au projet GenderedNews.
** Le projet GenderedNews **
Le projet GenderedNews vise à proposer de nouvelles méthodes pour mesurer et expliquer le niveau de biais de genre dans les médias en France. Ces biais peuvent être définis comme le fait que les médias d'information tendent d'une part à surpondérer les hommes par rapport aux femmes en termes de mentions et de citations, et d'autre part à attribuer aux femmes un rôle social spécifique impliquant souvent, entre autres, l'anonymat, une capacité d'action réduite dans la société et la confusion entre cette action et leur état matrimonial ou familial. De nombreuses études empiriques ont prouvé l'existence de ces biais et ont permis de mieux les comprendre à l'échelle internationale.
Cependant, la recherche sur cette question est souvent basée sur des données limitées en volume et produites par des ONG, des administrations ou des organismes de réglementation des médias. Ces données sont généralement traitées par des analyses de contenu manuelles qui ne permettent pas de rendre compte systématiquement des évolutions des biais sexistes dans les médias à long terme et sur un grand nombre de sources, ni d'expliquer ces biais en termes de variables telles que le financement des médias, la taille des salles de rédaction ou d'autres variables organisationnelles.
Le projet GenderedNews vise à fournir et à analyser des sources de données importantes et stables dans le temps ainsi qu'à explorer de nouvelles méthodes pour documenter les préjugés sexistes dans les médias. Il est basé sur un programme de recherche collaboratif entre un sociologue des médias et un informaticien ayant des compétences en études des médias, études de genre, traitement du langage naturel et collecte de données numériques. Il a également une dimension de partenariat importante dans la mesure où plusieurs médias importants sont associés et fournissent un accès à leurs données.
** Le doctorat : les biais de citation entre hommes et femmes dans l?information **
GenderedNews se concentre sur deux types de biais et deux mesures différentes de ces biais. Les biais d'échantillonnage se produisent par la sélection d'un échantillon biaisé de personnes mentionnées dans les médias. Ils peuvent être étudiés en comptant simplement combien d'hommes et de femmes ont accès à la visibilité publique d'un côté et en étudiant les modèles de cadrage des hommes et des femmes représentés de l'autre côté. Les biais de citation proviennent de la sélection d'un échantillon biaisé de personnes qui, en plus d'être visibles, sont autorisées à exprimer leurs opinions dans les médias. Ils peuvent également être étudiés en utilisant les deux approches: compter combien d'un côté et analyser comment de l'autre.
Dans le cadre du projet, le/la doctorant?e contribuera plus spécifiquement à l'étude des biais de citation. Cela impliquera les tâches et opérations de recherche suivantes:
- Analyse des données : les grands ensembles de données déjà constitués seront utilisés pour mesurer les biais d'approvisionnement dans l'actualité. Le/la doctorant?e utilisera notamment l'exploration de texte et les méthodes de NLP pour a) identifier les entités nommées dans le corpus, b) identifier les modèles de citation des sources dans les textes et c) étiqueter les entités nommées en fonction de leur sexe (sur la base des prénoms et des termes spécifiques au genre). Ces tâches permettront ensuite des analyses multivariées pour expliquer le niveau de diversité de genre atteint dans les différents médias analysés en fonction de variables sociologiques (par exemple, il sera possible de mesurer l'effet d'une augmentation de la proportion de femmes dans les rédactions sur le biais de genre ou l'effet d'une diminution du nombre de journalistes). - Entretiens : le/la doctorant?e engagé?e poursuivra également une recherche qualitative sur l?origine des éventuels biais de genre dans les organisations partenaires. Une première série d'enquêtes permettra de vérifier que les méthodes utilisées pour accéder au contenu des médias ne biaisent pas les résultats. Des entretiens seront menés avec les équipes techniques en charge du fonctionnement des API auprès des médias partenaires afin de mieux comprendre leur fonctionnement et d'identifier d'éventuels biais. Une deuxième série d'enquêtes se concentrera sur la compréhension de la hiérarchie de l'information dans ces médias et son influence possible sur les préjugés sexistes. Des entretiens seront menés avec des journalistes et des rédacteurs en chef pour comprendre ce qui rend un article d'actualité digne d'intérêt et comment les médias prennent en compte les questions de genre. Le but de ces interviews sera de comprendre comment les médias en tant qu'organisation contrôlent les préjugés sexistes dans leurs opérations quotidiennes. - Sur le plan théorique, cette thèse répondra à certaines questions qui étaient auparavant laissées dans l'ombre. Il s'agit notamment de la définition et de la mesure opérationnelle de la « diversité » dans l'actualité en relation avec les questions de genre pour la communauté des sciences sociales ainsi que la question du biais et de l'équité dans les algorithmes d'apprentissage automatique pour la communauté NLP.
En plus de la thèse et des publications scientifiques, le/la doctorant?e sera également impliqué?e dans le projet GenderedNews à différents niveaux:
- Superviser la collecte et le traitement des données avec les médias partenaires; - Contribuer à la production de nouveaux outils de mesure et de visualisation de la diversité des contenus et des sources dans les médias; - Contribuer à la diffusion des résultats auprès du grand public sur un site Internet servant de plateforme pour promouvoir une approche plus diversifiée de l'actualité.
** Environnement scientifique **
La thèse sera menée en tant que projet de recherche conjoint de l'équipe Régulations du laboratoire de recherche Pacte (https://www.pacte-grenoble.fr/page/regulations) et de l'équipe Getalp du laboratoire LIG (http://www.liglab.fr/en/research/research-areas-and-teams/getalp). Le/la doctorant?e recruté?e sera principalement hébergé?e au laboratoire de recherche Pacte pour un soutien quotidien et en partie au LIG. Le/la doctorant?e bénéficiera également du soutien du projet du Data Institute sur les médias sociaux et les sciences sociales (https://data-institute.univ-grenoble-alpes.fr/research/data-science-social-media-and-social- sciences/) et de la Chaire Algorithmic Society du MIAI qui encourage la recherche basée sur la collaboration des sciences sociales et de l?informatique pour contribuer à une meilleure compréhension du fonctionnement des algorithmes et à une évaluation critique des effets de l'IA dans la société (https://algorithmicsociety.github.io/).
**Comment postuler ?**
Les candidats doivent être titulaires d'un Master en sciences sociales ou en traitement du langage naturel (ou être sur le point d'en obtenir un). Ils devraient idéalement avoir une solide expertise dans les méthodes des sciences sociales et une bonne connaissance des méthodes d'exploration de texte et de traitement du langage. Ils doivent également avoir une très bonne connaissance des langues française et anglaise pour pouvoir traiter les données textuelles dans ces deux langues et mener des entretiens principalement en français.
Les candidatures sont attendues avant le 1er juillet 2020 et doivent être adressées à Gilles Bastin à gilles.bastin@iepg.fr et François Portet à Francois.Portet@imag.fr. Les candidat?es doivent joindre : - une lettre de candidature expliquant pourquoi ils/elles se considèrent capables de poursuivre ce projet de thèse, - leur dernier diplôme, - un CV. Ils/elles peuvent également ajouter des lettres de recommandation. Le comité de sélection informera les candidat?es de sa décision avant le 15 juillet 2020.
Si vous avez des questions sur le poste et le projet, veuillez contacter Gilles Bastin et / ou François Portet.
(2020-06-10) 2 post-docs positions at UTDallas, Texas, USA
POST-DOCTORAL POSITION #1
Center for Robust Speech Systems: Robust Speech Technologies Lab
Developing robust speech and language technologies (SLT) for naturalistic audio is the most challenging topic in the broader class of machine learning problems. CRSS-RSTL stands at the forefront of this initiative by making available the largest (150,000 hours) publicly available naturalistic corpus in the world. The FEARLESS STEPS corpus is the collection of multi-speaker time synchronized multi-channel audio from all of NASA’s 12 Apollo Manned Missions. Deployment of such ambitious corpora requires development of state-of-the-art support infrastructure using multiple technologies working synchronously to provide meaningful information to researchers from the science, technology, historical archives, and educational communities. To this end, we are seeking a post-doctoral researcher in the area of speech and language processing and machine learning. The researcher will collaboratively aid in the development of speech, natural language, and spoken dialog systems for noisy multi-channel audio streams. Overseeing digitization of analog tapes, community outreach and engagement, and assisting in cutting edge SLT research are also important tasks for the project.
Those interested should send an email with their resume and areas of interest to John.Hansen@utdallas.edu. More information can be found on our website: CRSS–RSTLab (Robust Speech Technologies Lab) at https://crss.utdallas.edu/
POST-DOCTORAL POSITION #2
Center for Robust Speech Systems: Cochlear Implant Processing Lab
Cochlear implants are one of the most successful solutions of replacing hearing sensation via an electronic device. However, the search for better sound coding and electrical stimulation strategies could be significantly accelerated by developing a flexible, powerful, portable speech processor for cochlear implants compatible with current smartphones/tablets. We are developing CCi-MOBILE, the next generation of such a research platform, one that will be more flexible and computationally powerful than clinical research devices that will enable implementation and long-term evaluation of advanced signal processing algorithms in naturalistic and diverse acoustic environments. To this end, we are seeking a post-doctoral researcher in the area of cochlear implant signal processing and embedded hardware/systems design. The researcher will collaboratively aid in the development of an embedded (FPGA-based) hardware (PCBs) for speech processing applications. Firmware development in Verilog and Java (Android) for DSP algorithms implementation is also an important task for the project.
Those interested should send an email with their resume and areas of interest to John.Hansen@utdallas.edu. More information can be found on our website: CRSS–CILab (Cochlear Implant Processing Lab) at https://crss.utdallas.edu/CILab/
If you know of any interested candidates looking for such a position, please share with them. They are welcome to get in touch with me <p.s.cesar@cwi.nl> concerning any questions prior to any formal application process.
(2020-06-18) Assistant/Postdoc level a TUWien, Austria
Are you interested to join a vibrant research environment in the center of Europe, as a Postdoc researcher or PhD student researcher, and work on exciting topics related to machine learning, recommender systems, or (multimedia) information retrieval?
If so, please have a look at the following two announcements with upcoming deadlines:
(2020-06-20) Two fully-funded PhD studentships in automatic speech recognition - University of Sheffield
Subject: Two fully-funded PhD studentships in automatic speech recognition - University of Sheffield
We are delighted to be able to offer two fully-funded PhD studentships in Automatic Speech Recognition at the Voicebase Centre of the University of Sheffield, to start in October 2020. The Voicebase studentship covers all fees and maintenance for 3 years at standard UK rates.
Topic 1: Semi-supervised Learning for Automatic Speech Recognition
(2020-06-30) PhD at Université Grenoble Alpes, France
L'Université Grenoble Alpes recrute une doctorante ou un doctorant avec un contrat de 3 ans entièrement financé à partir d'octobre 2020 dans le cadre du projet THERADIA.
*Le projet THERADIA*
Le projet THERADIA consiste à mettre au point un assistant thérapeutique virtuel qui constitue le relais et l?interface entre le patient et le thérapeute mais aussi les aidants qui gravitent autour du patient. Par un usage massif de différentes technologies d?intelligence artificielle, cet assistant empathique sera chargé d?adapter le traitement aux besoins du patient sous le contrôle du thérapeute, et de s?assurer de son suivi en interagissant avec les différents acteurs (thérapeute, patient, aidants) selon un mode conversationnel. Par rapport à un bot classique, l?objectif est de doter l?assistant d?une intelligence artificielle affective basée sur l?analyse des échanges verbaux et non verbaux (parole, prosodie et expressions du visage). L?assistant devra également être capable de synthétiser différents styles comportementaux pour interagir efficacement, et de résumer le fil d?interactions avec le patient pour restituer au thérapeute ou aux aidants un résumé des échanges et progrès réalisés. Validé d?un point de vue médico-économique dans le contexte de THERADIA, ces technologies pourront trouver de nombreux autres débouchés pour assister des humains amenés à sous-traiter à une intelligence artificielle les dimensions affectives de leurs interactions.
*Sujet de thèse* : Apprentissage profond et hybride pour la génération automatique de résumés multimédia d?observance de remédiation cognitive pour les aidants et cliniciens.
L?objectif de cette thèse de doctorat est de concevoir des méthodes permettant de générer un compte rendu pertinent pour les aidants et les orthophonistes synthétisant la prise en charge de patients souffrants de troubles cognitifs lors de séances de remédiations cognitives réalisées à domicile. La tâche de génération est donc de concevoir un système capable : - d'identifier, d'agréger, de sélectionner et de structurer les informations pertinentes à communiquer au destinataire - de transformer ces informations structurées en un document multimédia cohérent - d'adapter la réalisation vis-à-vis des critères de génération (type de destinataire, période à résumer, taille du texte)
Afin de gérer la grande complexité de la tâche deux approches complémentaires seront étudiées. Une approche experte (génération guidée par les experts médicaux) [Portet et al. 2009] et une approche neuronale de bout-en-bout apprise par renforcement (génération guidée par les lecteurs) [Brenon et al. 2018]. Une approche hybride sera également étudiée [Li et al. 2019]. Ces approches sont dépendantes d'un ensemble d'exemples disponibles pour induire le fonctionnement de ces différents choix. Malheureusement, ces données ne sont pas disponibles aujourd'hui. Basé sur nos derniers travaux, nous aborderons ce problème avec un modèle neuronal dans un cadre d'apprentissage faiblement supervisé qui est capable de tirer parti d'un faible nombre de données supervisées et d'un grand nombre de données non-supervisées. Dans notre cas les données supervisées seront celles acquises dans le projet et les données non supervisées seront obtenues auprès des partenaires (rapport d?entretien) et sur le web (textes comportant des émotions). L'état de l'art montre que des avancées importantes ont été faites en génération automatique de textes avec des modèles neuronaux. Cependant, ces avancées se sont appuyées sur des corpus de grande taille et sur des tâches isolées et bien définies. Dans notre cas, la difficulté porte principalement sur la sélection des informations en fonction du profil du destinataire, le manque de corpus adéquat et de mesure de performances. Un des objectifs de cette thèse sera de mettre en ?uvre des méthodes efficaces d'apprentissage faiblement supervisé [Qader et al. 2019], de renforcement et de collecte de données auprès des utilisateurs cibles du projet.
Enfin, l'évaluation de la génération automatique de textes est une tâche complexe. En effet, plusieurs dimensions linguistiques, sémantiques et applicatives doivent être prises en compte (grammaire, cohérence, émotion, pertinence, utilité). La qualité des sorties textuelles pourra être évaluée, d'une part, par des mesures automatiques sur corpus lors du développement de l'approche et, d'autre part, par des évaluations subjectives humaines (patients, aidants, experts) sur chaque itération majeure du système de génération.
*Environnement scientifique* La thèse sera menée au sein de l'équipe Getalp du laboratoire LIG (https://lig-getalp.imag.fr/). La personne recrutée sera accueillie au sein de l?équipe qui offre un cadre de travail stimulant, multinational et agréable. Les moyens pour mener à bien le doctorat seront assurés tant en ce qui concerne les missions en France et à l?étranger qu?en ce qui concerne le matériel (ordinateur personnel, accès aux serveurs GPU du LIG). La personne sera également amenée à collaborer avec plusieurs équipes impliquées dans le projet THERADIA, en particulier avec des chercheurs du GIPSA-lab situé également à Grenoble et les collaborateurs de l?entreprise SBT HumanMatter(s) basée à Lyon.
*Comment postuler ?* Les candidats doivent être titulaires d'un Master en informatique ou en traitement automatique du langage naturel (ou être sur le point d'en obtenir un). Ils doivent avoir une bonne connaissance des méthodes d?apprentissage automatique et idéalement une expérience en collecte et en évaluation impliquant l?humain. Ils doivent également avoir une très bonne connaissance des langues française et anglaise pour pouvoir traiter les données textuelles dans ces deux langues et mener des entretiens principalement en français. Une expérience dans le domaine de la génération automatique de textes serait un plus.
Les candidatures sont attendues au fil de l?eau et le poste sera ouvert jusqu?à ce qu?il soit pourvu. Elles doivent contenir : CV + lettre/message de motivation + notes master + lettre(s) de recommandations; et être adressées à François Portet (Francois.Portet@imag.fr) et Fabien Ringeval (Fabien.Ringeval@imag.fr).
*References* Brenon A., Portet F., Vacher M. (2018) Arcades : A deep model for adaptive decision making in voice controlled smart-homes. Pervasive and Mobile Computing, 49, pp.92-110 Li Y., Liang X., Hu Z. et al. (2018) Hybrid retrieval-generation reinforced agent for medical image report generation. Advances in Neural Information Processing Systems. p. 1530-1540. Portet F., Reiter E., Gatt A., Hunter J., Sripada S., Freer Y., Sykes C. (2009) Automatic generation of textual summaries from neonatal intensive care data. Artificial Intelligence, 173 (7-8), pp.789-816. Qader R., Portet F., Labbé C. (2019) Neural Text Generation from Unannotated Data by Joint Learning of Natural Language Generation and Natural Language Understanding Models, INLG2019
-- François PORTET Maître de conférences - Grenoble Institute of Technology Laboratoire d'Informatique de Grenoble - Équipe GETALP Bâtiment IMAG - Office 331 700 avenue Centrale Domaine Universitaire - 38401 St Martin d'Hères FRANCE
(2020-07-16) Early Stage Researcher / PhD student in an EU Marie Sklodowska-Curie Action (H2020-MSCA-ITN), Romania
We are hiring an Early Stage Researcher / PhD student in an EU Marie Sklodowska-Curie Action (H2020-MSCA-ITN) on the topic 'Designing and Engineering Multimodal Feedback to Augment the User Experience of Touch Input' under the supervision of Prof. Radu-Daniel Vatavu (http://www.eed.usv.ro/~vatavu)
The job will take place in the Machine Intelligence and Information Visualization Laboratory at Stefan cel Mare University of Suceava, Romania. The position is full-time (40 hours/week) for a fixed term of 3 years starting September 28, 2020.
(2020-07-20) Technical project manager, INRIA, Nancy, France
Inria is seeking a Technical Project Manager for a European (H2020 ICT) collaborative project called COMPRISE (https://www.compriseh2020.eu/).
COMPRISE is a 3-year Research and Innovation Action (RIA) aiming at new cost-effective, multilingual, privacy-driven voice interaction technology. This will be achieved through research advances in privacy-driven deep learning, personalized training, automatic data labeling, and tighter integration of speech and dialog processing with machine translation. The consortium includes academic and industrial partners in France, Germany, Latvia, and Spain. The project has been ongoing for 1.5 year, and it has received very positive feedback at its first review.
The successful candidate will be part of the Multispeech team at Inria Nancy (France). As the Technical Project Manager of H2020 COMPRISE, he/she will be responsible for animating the consortium in daily collaboration with the project lead. This includes orchestrating scientific and technical collaborations as well as reporting, disseminating, and communicating the results. He/she will also lead Inria?s software development and demonstration tasks.
Besides the management of COMPRISE, the successful candidate will devote half of his/her time to other activities relevant to Inria. Depending on his/her expertise and wishes, these may include: management of R&D projects in other fields of computer science, involvement in software and technology development and demonstration tasks, building of industry relationships, participation in the setup of academic-industry collaborations, support with drafting and proofreading new project proposals, etc.
Ideal profile: - MSc or PhD in speech and language processing, machine learning, or a related field - at least 5 years' experience after MSc/PhD, ideally in the private sector - excellent software engineering, project management, and communication skills
Application deadline: August 30, 2020
Starting date: October 1, 2020 Duration: 14 months Location: Nancy, France Salary: from 2,300 to 3,700 EUR net/month, according to experience
