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ISCApad #238 |
Friday, April 13, 2018 by Chris Wellekens |
6-1 | (2017-12-03) Machine Learning Engineer, Speech Recognition, Aja-la studios, Green Richmond UK Machine Learning Engineer, Speech Recognition developing acoustic and language models, and related algorithms, for our suite of proprietary speech recognition products for a broad library of under-resourced languages. This role provides a unique opportunity to pursue research and commercialization of speech recognition for under-resourced languages. in and/or demonstrate experience working with under-resourced languages, an interest in working on the entire R&D/product-development cycle. •Masters or PhD in an analytical discipline through which you have acquired a strong knowledge of topics including o Theory and practice of speech recognition and/or speech processing (LSCVR) o Signal Processing/Pattern Recognition o Probability theory o Bayesian inference o Machine learning and related topics • Strong software development skills o Required: C/C++, Python, CUDA/Nsight IDE, shell scripting, Perl, Github/SVN o Optional/Additional: Java/Android/Gradle/Android Studio, Objective C/Xcode/Cocos2dx • Speech processing, Neural Network and Natural Language platforms and libraries o Kaldi, KenLM, OpenFST, and HTS o Theano, PDNN, pyTorch, TensorFlow • Operating Systems: Unix/Linux/Mac OS 1 The Green Richmond, TW9 1PL UK www.ajalastudios.com
amongst other benefits.
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6-2 | (2017-12-04) Machine Learning Engineer, Speech Synthesis , Aja-la studios,Green Richmond UK Machine Learning Engineer, Speech Synthesis topics including o Theory and practice of speech synthesis and/or speech processing, e.g. vocoding o Signal Processing/Pattern Recognition o Probability theory o Bayesian inference o Machine learning and related topics • Strong software development skills o Required: C/C++, Python, CUDA/Nsight IDE, shell scripting, Perl, Github/SVN o Optional/Additional: Java/Android/Gradle/Android Studio, Objective C/Xcode/Cocos2dx • Speech processing, Neural Network and Natural Language platforms and libraries o Festival, HTK, and HTS o Theano, PDNN, pyTorch, TensorFlow • Operating Systems: Unix/Linux/Mac OS 1 The Green Richmond, TW9 1PL UK www.ajalastudios.com amongst other benefits.
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6-3 | (2017-12-03) Research Assistant/Associate in Speech Processing, at Cambridge University Engineering Department, Cambridge, UK. Research Assistant/Associate in Speech Processing, at Cambridge University Engineering Department, Cambridge, UK.
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6-4 | (2017-12-05) One-year post-doctoral position in speech production, GIPSA, Grenoble, France One-year post-doctoral position in speech production, in the framework of the StopNCo ANR project (http://www.agence-nationale-recherche.fr/Project-ANR-14-CE30-0017 <http://www.agence-nationale-recherche.fr/Project-ANR-14-CE30-0017>), starting from March 2018 (at the latest in October 2018).
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6-5 | (2017-12-06) PhD Position in Social Signal Processing for Multi-Sensor Conversation Quality Modeling, Delft University, The Netherlands Job Link: https://tinyurl.com/MINGLEPhD PhD Position in Social Signal Processing for Multi-Sensor Conversation Quality Modeling Location: Delft University of Technology, The Netherlands Deadline: January 12 2018 (see below for application procedure) Project Description: An important but under-explored problem in computer science is the automated analysis of conversational dynamics in large unstructured social gatherings such as networking or mingling events. Research has shown that attending such events contributes greatly to career and personal success. While much progress has been made in the analysis of small pre-arranged conversations, scaling up robustly presents a number of fundamentally different challenges. Unlike analysing small pre-arranged conversations, during mingling, sensor data is seriously contaminated. Moreover, determining who is talking with whom is difficult because groups can split and merge at will. A fundamentally different approach is needed to handle both the complexity of the social situation as well as the uncertainty of the sensor data when analysing such scenes. The successful applicants will develop automated techniques to analyse multi-sensor data (video, acceleration, audio, etc) of human social behavior. They will work as part of a team on the NWO Funded Vidi project MINGLE (Modelling Group Dynamics in Complex Conversational Scenes from Non-Verbal Behaviour). They will have the opportunity to interact with researchers from both computer science and social science both locally and internationally. The main aim of the project is to address the following question: How can multi-sensor processing and machine learning methods be developed to model the dynamics of conversational interaction in large social gatherings using only non-verbal behaviour? The two project advertised focus on developing novel computational methods to measure conversation quality (e.g. involvement, rapport) from multi-sensor streams in crowded environments
Job requirements: We are looking students who have recently completed or expect very soon an MSc or equivalent degree in computer science, electrical/electronic engineering, applied mathematics, applied physics, or a related discipline. Experience in the following or related fields are preferred: signal/audio/speech processing, computer vision, machine learning, and pattern recognition. Some experience with embedded systems is a bonus, though not necessary.
The successful applicant will have:- good programming skills;- curiosity and analytical skills;- the ability to work in a multi-disciplinary team;- motivation to meet deadlines;- an affinity with the relevant social science research;- good oral and written communication skills;-proficiency in English;- an interest in communicating their research results to a wider audience; Institution:
The department Intelligent Systems is part of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at Delft University of Technology. The faculty offers an internationally competitive interdisciplinary setting for its 500 employees, 350 PhD students and 1700 undergraduates. Together they work on a broad range of technical innovations in the fields of sustainable energy, quantum engineering, microelectronics, intelligent systems, software technology, and applied mathematics.??? The Pattern Recognition and BioInformatics Group is one of five groups in the department, consisting of 7 faculty and over 20 postdoc and PhD students. Within this group, research is carried out in three core subjects; pattern recognition, computer vision, and bioinformatics. One of the main focuses of the group is on developing tools and theories, and gaining knowledge and understanding applicable to a broad range of general problems but typically involving sensory data, e.g. times signals, images, video streams, or other physical measurement data. For information about the TU Delft Graduate School, please visit www.phd.tudelft.nl.???? Application Procedure: Interested applicants should send an up-to-date curriculum vitae, degree transcripts, letter of application, and the names and the contact information (telephone number and email address) of two references to Hr-eemcs@tudelft.nl with the subject heading '[MINGLE PhD]'.
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6-6 | (2017-12-08) PhD grant at IRISA, Rennes France L'équipe Expression de l'IRISA recrute un.e doctorant.e en Détails de l'offre : https://www-expression.irisa.fr/files/2017/12/these_TREMoLo_2017.pdf - CV détaillé* - lettre de motivation* - relevés de notes (avec classement si possible)* - contacts pour recommandation* - rapport(s) de stage recherche. gwenole.lecorve@irisa.fr. Gwénolé Lecorvé.
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6-7 | (2017-12-15) Internship 1 at LIA, Avignon, France Adaptation des réseaux de neurones profonds pour les systèmes de transcription de la parole prononcés dans un enregistrement audio ou vidéo. Les systèmes de RAP les plus robustes reposent souvent sur une architecture multi-passe (Gauvain et Lee 1994) (Gales 1998), chaque passe permettant d’obtenir une transcription du signal audio qui se veut de meilleure qualité que la précédente. Ainsi, dans certains cas, les sorties de la passe précédente sont utilisées pour adapter les modèles de la passe en cours. L’idée de cette adaptation est d’obtenir des modèles spécialisés à l’enregistrement, et donc d’être plus robuste face aux « variabilités » des enregistrements audio (conditions acoustiques différentes, locuteurs inconnus, spontanéité de la parole, bruits de l’environnement...). Plus précisément, le stage explorera l’adaptation non-supervisée des réseaux de neurones profonds. Un des principaux challenges est d’utiliser les réseaux de neurones en tant que modèle de langage et de pouvoir les adapter à une première transcription issue du décodage. programmation (C/C++ et/ou Python). Des notions en Traitement Automatique de la Langue, Traitement de la parole ou Apprentissage automatique serait un plus. Computer Speech and Language (CSL), 1998. Gauvain, Jean-Luc, et Chin-Hui Lee. «Maximum a posteriori estimation for multivariate Gaussian mixture observations of Markov chains.» IEEE Transactions on Speech and Audio Processing (TASP), 1994.
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6-8 | (2017-12-15) Internship 2 at LIA Avignon, France Résumé vidéo automatique par contextualisation de vidéo à partir d’un texte les présentent de façon aussi concise que possible. Dans ce stage nous nous intéressons aux méthodes de résumé vidéo par extraction basées sur l’analyse du texte [Li11, Trione14, Favre15]. représentation intermédiaire textuelle : le contenu audio de la vidéo (et parfois les textes incrustés) sont extraits, transcrits puis résumés. Ce résumé texte est ensuite utilisé pour assembler un résumé vidéo. L’objectif général du stage est d’explorer des méthodes de contextualisation de vidéos ou d’images à partir de la transcription texte. Cette contextualisation doit aider à la composition du résumé vidéo final. (C/C++ et/ou Python). Des notions en Traitement Automatique de la Langue ou Apprentissage automatique seraient un plus. of the 19th ACM international conference on Multimedia (pp. 1573-1576). ACM. [Trione14] Trione, J. (2014). Extraction methods for automatic summarization of spoken conversations from call centers (Méthodes par extraction pour le résumé automatique de conversations parlées provenant de centres d’appels)[in French]. In Proceedings of TALN 2014 (Volume 4: RECITAL-Student Research Workshop) (Vol. 4, pp. 104-111). [Favre15] Favre, B., Stepanov, E. A., Trione, J., Béchet, F., & Riccardi, G. (2015). Call Centre Conversation Summarization: A Pilot Task at Multiling 2015. In SIGDIAL Conference (pp. 232-236).
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6-9 | (2017-12-13) Internship and PhD position at Telecom-ParisTech and LTCI lab, Paris, France
Internship and PhD position in machine learning for multimodal engagement analysis in human-robot interactions (HRI)
Telecom ParisTech [1], LTCI lab [2]
Salary: according to background and experience
*Position description*
The internship/PhD project will take part in a collaboration between Softbank Robotics and Télécom ParisTech on the topic of engagement analysis in interactions of humans with Softbank?s robots. The role of the intern/PhD student will consist in developing robust machine learning systems able to effectively take advantage of the multimodal signals acquired by the robot?s sensors during its interaction with a human. The work will include: - the design of appropriate elicitation protocols and multimodal data acquisition procedures ; - the development of multimodal feature learning and dynamic classification procedures capable of handling noisy observations with missing values, especially exploiting deep learning techniques ; - the evaluation of the system in realistic scenarios involving end-users. The PhD project will be hosted at Telecom ParisTech department of images, data and signals of [3], jointly by the social computing [4] and the audio data analysis and signal processing [5] teams.
As a minimum requirement, the successful candidate will have:
? A Master?s degree (possibly to be granted in 2018) in one of the following areas: computer science, artificial intelligence, machine learning, signal processing, affective computing, applied mathematics ? Excellent programming skills (preferably in Python) ? Good command of English
The ideal candidate will also (optionally) have: ? Knowledge in deep learning techniques
-- More about the position ? Place of work: Paris, France ? For more information about Télécom ParisTech see [1]
-- How to apply Applications are to be sent to Chloé Clavel [6], Giovanna Varni [7] and Slim Essid [8] by email (using <firstname.lastname>@telecom-paristech.fr)
The application should be formatted as a single pdf file and should include: ? A complete and detailed curriculum vitae ? A letter of motivation ? Academic records of the last two years ? The names and addresses of two referees
[1] http://www.tsi.telecom-paristech.fr [2] https://www.ltci.telecom-paristech.fr/?lang=en [3] http://www.tsi.telecom-paristech.fr/en/ [5] http://www.tsi.telecom-paristech.fr/aao/en/ [6] https://clavel.wp.mines-telecom.fr/ [7] http://sites.google.com/site/gvarnisite/ [8] http://www.telecom-paristech.fr/~essid
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6-10 | (2017-12-16) Position at INA, Bry/Marne, France L’Institut national de l’audiovisuel (INA), entreprise publique audiovisuelle et numérique, collecte, sauvegarde et transmet le patrimoine audiovisuel français. Dans une démarche d’innovation tournée vers les usages, l’INA valorise ses contenus et les partage avec le plus grand nombre : sur ina.fr pour le grand public, sur inamediapro.com pour les professionnels, à l’InaTHÈQUE pour les chercheurs. L’institut développe ainsi des offres et des services afin de se rapprocher de ses usagers et clients, en France comme à l’international.
Son département Recherche et Innovation soutient une culture de l’innovation forte et ambitieuse. Notre technologie Ina-Signature (technologie de « fingerprint ») – issue de la R&D de l’Ina - a su s’imposer auprès de clients renommés, grâce à une stratégique axée sur la performance et la qualité. Notre offre continue à évoluer, avec la démocratisation du SAAS (software as a service) et du CLOUD.
Dans le cadre de votre mission, rattaché/e au Chef du service de la Recherche, vous garantissez la conception, la mise en oeuvre, l'intégration ou l'adaptation des technologies d’apprentissage automatique, d’analyse et de fusion de données dans le cadre des projets de Recherche pour l’expérimentation de nouveaux usages de valorisation des contenus.
A ce titre, vous serez en charge de :
1 – Effectuer de la Recherche scientifique et technologique - Définir les axes de recherche et développement liés à cette thématique ; - Concevoir, implémenter, tester, évaluer des outils technologiques innovants dans le cadre des usages existants ou pressentis de l’Institut ; - Collaborer avec l’ensemble des acteurs internes et externes du département ; - Participer à la stratégie de recherche et développement du service ; - Encadrer des stagiaires et à terme des doctorants ; - Rédiger ou participer à la rédaction d’articles scientifiques et présenter ces articles dans des colloques ; - Démontrer les travaux de recherche lors de colloques, séminaire ou salons : - Participer à la rédaction des documents liés à l’activité (rapports d’activité, livrables des projets en particulier).
2 – Assurer une R&D au service de l’Institut - Proposer, préparer, coordonner, participer à des projets de Recherche et Développement internes en lien avec les services opérationnels ; - Proposer, piloter, participer à des actions de concertation et de réflexion internes et groupes de travail.
3 – Réaliser des partenariats - Proposer, préparer, coordonner, participer à des projets de Recherche et Développement collaboratifs, nationaux ou internationaux en lien avec des partenaires académiques, institutionnels ou industriels ; - Proposer, coordonner, participer à des instances de coopération scientifique et technologique (COMUE, Pôles de compétitivité, Groupes de recherche).
4 – Collaborer au management fonctionnel - Participer à la coordination du service (réunions de coordination) ; - Participer aux tâches de gestion des ressources informatiques et techniques du service ; - Participer à la vie du service (réunions de service, suivis d’activité, rapports).
Profil : Vous justifierez d'un doctorat dans le domaine de l’apprentissage automatique et/ou de l’analyse de données ou d'un parcours professionnel admis en équivalence.
Complété de compétences en : - Maîtrise et expérience dans le(s) domaine(s) suivants : apprentissage automatique (Deep Learning), analyse et fusion de données, analyse de l’image et/ou de l’audio, développement informatique - Bonne pratique en recherche académique et/ou industrielle ; - Pratique en publications scientifiques ; - Bonne connaissance et pratique de projets collaboratifs ; - Connaissance du paysage audiovisuel français ; - Connaissance du monde académique ; - Maîtrise des outils bureautiques ; - Intérêt pour le monde de l’audiovisuel et des médias ; - Intérêt pour les Sciences Humaines et Sociales et les Humanités Numériques
Des qualités d’analyse et de synthèse, de créativité et d’imagination, de force de proposition, relationnelles et d’esprit d’équipe seront vos meilleurs atouts pour réussir dans le poste.
Modalités du poste : - Contrat : CDI - Statut : Cadre - Poste à pourvoir : au plus vite - Salaire : selon expérience - Clôture de la consultation : 31 janvier 2018 - Contact : jcarrive@ina.fr - Localisation géographique : Bry S/Marne (94)
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6-11 | (2017-12-16) Post-doc position at Uniklinik RWTH Aachen (Germany) We are looking at the Uniklinik RWTH Aachen (Germany) for a postdoctoral researcher in
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6-12 | (2017-12-13) PhD position in Conversational systems and Social robotics, KTH, Stockholm, Sweden PhD position in Conversational systems and Social robotics, KTH, Sweden 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 centre 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. We are looking for a doctoral student that will work on situated spoken interaction between humans and robots, under the supervision of Assoc. Prof. Gabriel Skantze, at the Department of Speech Music and Hearing. A central research question will be how social robots should adapt their conversational behavior to the users' level of attention, understanding and engagement. This means that the robot must be able to monitor gaze and feedback behaviour from the user, and then for example adjust the pace of information delivery, in real time. The work will involve implementation of components for conversational systems, collecting data and doing experiments with users interacting with the system, and using this data to build models of the users' behaviours. Applicants should have a Master degree (or similar) in a subject relevant for the research, such as computer science, language technology, or cognitive science. Applicants are expected to have good skills in programming, and knowledge in either experimental methods and statistics, or machine learning. Applicants must be strongly motivated for doctoral studies, possess the ability to work independently and perform critical analysis, and possess good levels of cooperative and communicative abilities. Good command of English, in writing and speaking, is a prerequisite for presenting research results in international periodicals and at conferences. We also expect applicants to have a deep interest in spoken language interaction between humans and between humans and machines. The position is mainly a research position for 4-5 years, with a small fraction of departmental duties (e.g. teaching). The starting date is open for discussion, though ideally we would like the successful candidate to start as soon as possible. For more information, see: https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:178626/where:4/
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6-13 | (2017-12-13) 2 funded PhD positions in interactive virtual characters and social robots at KTH, Stockholm, Sweden ** 2 funded PhD positions in interactive virtual characters and social robots at KTH, Sweden**
Embodied Social Agents Lab
KTH Royal Institute of Technology
Stockholm, Sweden
Deadline: 15th January 2018
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 Embodied Social Agents Lab (http://www.csc.kth.se/~chpeters/ESAL/) led by Dr. Christopher Peters aims to develop virtual characters and other systems capable of interacting socially with humans for real-world application to areas such as education. The lab is already involved in a number of local and international initiatives involving virtual characters, social robots and education. It is based out of the Visualization Studio (VIC) at KTH, a research, teaching and dissemination resource with some of the most advanced interactive visualization technologies in the world, supporting platforms for interacting with sophisticated virtual characters.
JOB DESCRIPTION
Two PhD positions are available in the area of interactive virtual characters and social robots for application to education. Research in this area brings together multidisciplinary expertise to address new challenges and opportunities in the area of virtual characters, based on real-time computer graphics and animation techniques, to investigate multimodal and natural interaction for both individuals and groups, multimodal generation of expressions, individualization of behaviour and effects of embodiment (appearance, virtual versus physical objects). Applications are the design of interactive virtual and physical systems for educational purposes.
The topics to be pursued respectively in the PhDs are:
1. Compliant Small Group Behaviour (ref: ESR5)
Develop socially compliant behaviours allowing agents to join and leave free-standing formations based on their varying roles as teachers, teaching assistants and learners in pedagogical scenarios. Investigate the impact of variations in the artificial behaviour of agents on the efficacy of pedagogical approaches and potential for application to mobile robots through virtual replicas.
2. Impact of Appearance Customisation on Interaction (ref: ESR15)
Investigate technological approaches for customising the appearances and behaviours of avatars (user controlled virtual characters and robot replicas) in relation to their users and assess the impact on interactions during learning scenarios.
Both of the PhDs involve crossovers between virtual and augmented reality, virtual characters and mobile social robots and take place within the Horizon 2020 Marie Sklodowska Curie European Training Network ANIMATAS.
ANIMATAS will establish a leading European Training Network (ETN) devoted to the development of a new generation of creative and critical research leaders and innovators who have a skill-set tailored for the creation of social capabilities necessary for realising step changes in the development of intuitive human-machine interaction (HMI) in educational settings. 15 early-stage researcher (ESR) positions are available within ANIMATAS.
The successful candidates will participate in the network?s training activities offered by the European academic and industrial participating teams. PhD students will have the opportunity to work with the partners of the ANIMATAS project, such as Uppsala University, Jacobs University Bremen, Institut Mines-Télécom, University of Wisconsin-Madison, Pierre et Marie Curie University and Softbank Robotics, with possible opportunities for secondments at these institutions according to the ESR.
QUALIFICATIONS
The candidates must have an MSc degree in computer science or related areas relevant to the PhD topics. Good programming skills are required. A background in computer graphics and animation techniques or similar areas is appreciated. The PhD positions are highly interdisciplinary and require an understanding and/or interest in psychology and social sciences. The applicant should have excellent communication skills and be motivated to work in an interdisciplinary environment involving multiple stakeholders across academia, industry and education. An excellent level of written and spoken English is essential.
Read more about eligibility requirements at this link: http://animatas.isir.upmc.fr
The positions are for four years.
HOW TO APPLY
To apply, candidates must submit their CV, a letter of application, two letters of reference and academic credentials to the ANIMATAS recruitment committee: Mohamed Chetouani (network coordinator), Ana Paiva and Arvid Kappas at contact-animatas@listes.upmc.fr, and to the main supervisor of the research project of interest (Christopher Peters, chpeters@kth.se). All applications should be made in English.
Please include the keyword ?ANIMATAS? somewhere in the subject line and specify which project you are applying for (ESR5 or ESR15).
The application deadline is 15th January 2018
Information about the positions can be provided by Dr. Christopher Peters, chpeters@kth.se
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6-14 | (2018-01-09) Two postdoc positions at IDIAP, Martigny, Switzerland ===========================================
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6-15 | (2018-01-10) Postdocs at Monash University, Melbourne, Australia The Faculty of Information Technology (https://www.monash.edu/it) at Monash University in Melbourne Australia is establishing a new group in HCI and creative technologies. We invite accomplished and creative PhDs to apply for a 3-year postdoctoral fellowship in multimodal interfaces and behavior analytics. The selected candidate will join a rapidly expanding multidisciplinary group with expertise in areas such as mobile and multimodal-multisensor interfaces, agent-based conversational interfaces, brain-computer and adaptive interfaces, wearable and contextually-aware personalized interfaces, education and health interfaces, data analytics for predicting user cognition and health status, and other topics. We are especially interested in adding faculty in these preferred areas: (1) Wearable, contextually-aware and personalized interfaces (2) Mobile and multimodal-multisensor interfaces, including fusion-based ones (3) Data analytics for predicting user emotion, cognition, and health status (4) Agent-based conversational dialogue interfaces (5) Brain-computer and adaptive interfaces This position involves research on predicting user cognition and health status, based on analysis of different modalities (e.g., speech, writing, images, sensors) during naturally occurring activities. These analyses involve exploring predictive patterns at the signal, activity pattern, lexical, and/or transactional levels. The ideal candidate would be an initiating researcher with a strong publication record who is interested in pioneering in emerging research areas. He/she would have an interest in developing new technologies to identify users? cognitive and health status, and using this information to develop personalized and adaptive interfaces that promote learning, performance, and health. Requirements: ? PhD in computer science, engineering, information sciences, cognitive or linguistic sciences, or related field ? Training in HCI, multimodal interfaces, data science and analytics, modeling human behavior & communication ? Experience collecting and analyzing speech, images, handwriting, and/or other sensor data ? Experience applying machine learning/deep learning, empirical/statistical, linguistic, or hybrid analysis methods ? Interest in human cognition and educational technologies, and/or health and mental health technologies ? Strong interpersonal, teamwork, communication and writing skills ? Ability to work with diverse partners? domain experts (teachers, clinicians), industry, undergraduate/graduate students ? Prefer candidate with 2-3 years post-PhD research or work experience HCI Group: The HCI group designs, builds, and evaluates state-of-the-art interface technologies. Our multidisciplinary interests span computer science and engineering, cognitive and learning sciences, communications, health, media design, and other topics. We are interested in applications such as health, education, communications, personal assistance, and digital arts. The HCI group has partnerships with CSIRO-Data61 and industry. The HCI area director is Dr. Sharon Oviatt, an ACM Fellow and international pioneer in human-centered, mobile, and multimodal interfaces (see https://www.monash.edu/it/our-research/graduate-research/scholarship-funded-phd-research-projects/projects/human-centred-mobile-and-multimodal-interfaces) Monash is Australia?s largest university, and ranks in the top 60 universities worldwide, with Computer and Information Systems rated in the top 70 worldwide (QS World University rankings 2018). In addition to growing rapidly in human-centered computing, software, and cyber-security, it includes data science and machine learning, artificial intelligence and robotics, computational biology, social computing, and basic computer science. Experimental Labs & Design Spaces: The university has made recent strategic investments in facilities for prototyping innovative concepts, collecting and analyzing data, and displaying digital installations and interactive media?including sensiLab (supporting tangible, wearable, augmented and virtual reality, multimodal-multimedia, maker-space), Immersive Visualization platform and Analytics lab, the Centre for Data Science, and the ARC Centre of Excellence on Integrative Brain function (pioneering new multimodal imaging techniques for data exploration). The university currently is investing in HCI group facilities for prototyping and developing new mobile, multimodal and multisensor interfaces, analyzing human multimodal interaction (e.g., whole-body activity, speech), and predicting users? cognitive and health status. Melbourne Area: Melbourne recently has been rated the #1 city worldwide for quality of life (see Economist & Guardian, http://www.economist.com/blogs/graphicdetail/2016/08/daily-chart-14 and https://www.theguardian.com/australia-news/2016/aug/18/melbourne-wins-worlds-most-liveable-city-award-sixth-year-in-a-row), with excellent education, healthcare, infrastructure, low crime, and exceptional cuisine, cultural activities, and creative design. The regional area is renowned for its dramatic coastline, extensive parks, exotic wildlife, and Yarra Valley wine region. Position & Compensation: This position is full-time for 3 years, with competitive salary (Academic level B-6, $119,683 AUD) and benefits, including 17% superannuation retirement fund, health insurance options, relocation, and seed funds for equipment and travel. Start date is negotiable after April 1, 2018. For enquiries, contact Oviatt@incaadesigns.org. To apply: To submit an online application: http://careers.pageuppeople.com/513/cw/en/job/571150/research-fellow-multimodal-interfaces-behaviour-analytics Required application materials include: (1) cover letter (indicating date of availability); (2) current CV with publication list, research and teaching interests, and 3 references with email/phone contact; (3) graduate transcripts; and (4) three representative publications. Monash has a Women in IT Program, and participates in the Athena Swan Charter to enhance gender equality. We welcome female, minority and international applicants.
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6-16 | (2018-01-11) Postdoc position at IDIAP, Martigny, Switzerland We have a new opening for a post-doctoral researcher at Idiap Research Institute. It is
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6-17 | (2018-01-18) (SENIOR) SPEECH SCIENTIST at Voicebox, München, Germany (SENIOR) SPEECH SCIENTIST
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6-18 | (2018-01-18) 3 permanent(indefinite tenure) faculty positions at Telecom ParisTech, Paris, France Telecom ParisTech has three new permanent(indefinite tenure) faculty positions:
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6-19 | (2018-01-20) Machine learning Software Engineer, Adobe Research - Speech Recognition, San Jose, CA,USA Machine learning Software Engineer, Adobe Research - Speech Recognition
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6-20 | (2018-01-25) 2018 PHD RESEARCH FELLOWSHIPS at University of Trento , Italy 2018 PHD RESEARCH FELLOWSHIPS ( ML/Dialogue/Language/Speech)
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6-21 | (2018-01-25) PhD student in Robot-assisted Language Learning at KTH Royal Institute of Technology, Stockholm, Sweden PhD student in Robot-assisted Language Learning at KTH Royal Institute of Technology, Stockholm, Sweden
Ending January 31st 2018.
Olov Engwall
Professor in Speech Communication
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6-22 | (2018-01-26) Poste MCF à l'ENSIMAG, Grenoble, France Poste MCF à l'ENSIMAG.
Ecole de rattachement : ENSIMAG
Site web de l?école : http://ensimag.grenoble-inp.fr/
Contact de l?école : Jean-Louis.Roch@grenoble-inp.fr, Olivier.Francois@grenoble-inp.fr
Profil d?enseignement :
L?Ensimag recrute un maître de conférences en mathématiques appliquées ou en informatique
afin de développer les enseignements d?apprentissage statistique, d?intelligence artificielle, de
visualisation de données, de calcul haute performance ou de « big data ». Le dossier de
candidature devra faire apparaître le caractère ?interdisciplinaire? du candidat, sa capacité à
prendre des responsabilités au sein de la structure, ainsi qu?une liste conséquente de travaux
ou publications en relation avec une ou plusieurs branches de la science des données. Outre la
formation aux sciences des données (synthèse de programmes à partir de données, aide à la
décision), la personne recrutée devra s?investir dans les enseignements du tronc commun
Ensimag (1ère année et environ 75% des filières de la 2ème année) qui constitue le socle de nos
élèves ingénieurs. Elle sera amenée à s'investir et prendre des responsabilités dans des
parcours de l?Ecole tels que le « mastère big data » ou le master « Data Science ». En
partenariat avec des industriels, la personne recrutée pourrait superviser l?organisation de «
challenges » et de « hackatons » afin d?enrichir les contacts de l?Ecole dans le domaine de
l?intelligence artificielle et des « big data ». En collaboration avec les équipes pédagogiques
concernées, elle devra s?impliquer dans le montage d?enseignements par projets et la
formation par le Numérique.
RECHERCHE
Laboratoire d?accueil : LIG / LJK
Site web du laboratoire : http://www.liglab.fr/
Contact du laboratoire : Eric Gaussier (eric.gaussier@imag.fr), LIG
Stéphane Labbé (stephane.labbe@imag.fr), LJK
Profil de recherche :
Le candidat effectuera ses recherches dans le domaine de l?intelligence artificielle ou de la
science des données, et montrera son ouverture aux différentes approches possibles dans ce
domaine. Les thématiques privilégiées sont l?apprentissage sur données complexes, structurées
ou non structurées, l?apprentissage profond et les réseaux de neurones et en particulier les
problématiques d?optimisation, de causalité, de capacité de généralisation et leur analyse
mathématique. Parmi les applications de l?apprentissage et de l?apprentissage profond, un
intérêt particulier est porté au traitement du signal et de l?image, à l?apprentissage de
représentation, à l?apprentissage avec des données multimédia, des données langagières pour
des problématiques issues du traitement du langage naturel, les thématiques de transparence
des mécanismes d?apprentissage, ainsi que les applications en biologie, santé, sciences
humaines, réseaux sociaux, physique, environnement, etc.
Le recrutement renforcera les liens entre le LIG et le LJK dans les domaines de la science des
données et de l?apprentissage automatique. Les deux laboratoires sont localisés sur le campus
de Saint Martin d?Hères et ont des collaborations actives, en particulier au sein de l?axe du
traitement de données et de connaissance à large échelle (équipes AMA, GETALP, MRIM,
SLIDE), des équipes PERVASIVE, TYREX du LIG et au sein du département Proba-Stat (équipes
DAO, SVH, MISTIS, FIGAL) et de l?équipe THOTH du LJK. Parmi les projets communs entre les
deux laboratoires, on peut également citer les problèmes de prédiction et de classification avec
des données structurées de type fonctionnelles, le transport optimal pour l?apprentissage, les
problèmes de parcimonie et de régularisation pour l?apprentissage multitâches et leur
résolution par des méthodes d?optimisation stochastique. La personne recrutée montrera sa
capacité à jouer un rôle actif dans les projets contractuels académiques (ANR, FUI, PFIA, EU...)
et industriels sur ces thèmes très porteurs.
ACTIVITES ADMINISTRATIVES
Spécificités du poste ou contraintes particulières :
Activités administratives liées aux fonctions de maître de conférences : responsabilités d?unité
d?enseignement, responsabilités de filières ou d?année.
Compétences attendues :
Savoir : Enseignement de l?informatique, de l?intelligence artificielle et de la science
des données
Savoir-faire : Pédagogie et responsabilités dans l?Ecole
Savoir-être : Travail en équipe
pdf
Intelligence artificielle, Science des données, Big data, Apprentissage
------------------------
Laurent Besacier
Professeur à l'Univ. Grenoble Alpes (UGA)
Laboratoire d'Informatique de Grenoble (LIG)
Membre Junior de l'Institut Universitaire de France (IUF 2012-2017)
Responsable équipe GETALP du LIG
Directeur de l'école doctorale (ED) MSTII
-------------------------
!! Nouvelles coordonnées !!: LIG
Laboratoire d'Informatique de GrenobleBâtiment IMAG 700 avenue Centrale Domaine Universitaire - 38401 St Martin d'Hères Pour tout contact concernant ED MSTII: passer par ed-mstii@univ-grenoble-alpes.fr
Nouveau tel: 0457421454
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6-23 | (2018-01-27) Post-doctoral researcher at Idiap Research Institute, Martigny, Switzerland Post-doctoral researcher at Idiap Research Institute. It is a joint position with the Swiss Center for Electronics and
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6-24 | (2018-01-27) Post Doctoral Position (12 months) at INRIA Nancy, France Post Doctoral Position (12 months) Natural language processing: automatic speech recognition system using deep neural networks without out-of-vocabulary words _______________________________________ - Location:INRIA Nancy Grand Est research center, France
- Research theme: PERCEPTION, COGNITION, INTERACTION
- Project-team: Multispeech
- Scientific Context:
More and more audio/video appear on Internet each day. About 300 hours of multimedia are uploaded per minute. In these multimedia sources, audio data represents a very important part. If these documents are not transcribed, automatic content retrieval is difficult or impossible. The classical approach for spoken content retrieval from audio documents is an automatic speech recognition followed by text retrieval.
An automatic speech recognition system (ASR) uses a lexicon containing the most frequent words of the language and only the words of the lexicon can be recognized by the system. New Proper Names (PNs) appear constantly, requiring dynamic updates of the lexicons used by the ASR. These PNs evolve over time and no vocabulary will ever contains all existing PNs. When a person searches for a document, proper names are used in the query. If these PNs have not been recognized, the document cannot be found. These missing PNs can be very important for the understanding of the document.
In this study, we will focus on the problem of proper names in automatic recognition systems. The problem is how to model relevant proper names for the audio document we want to transcribe.
- Missions:
We assume that in an audio document to transcribe we have missing proper names, i.e. proper names that are pronounced in the audio document but that are not in the lexicon of the automatic speech recognition system; these proper names cannot be recognized (out-of-vocabulary proper names, OOV PNs). The purpose of this work is to design a methodology how to find and model a list of relevant OOV PNs that correspond to an audio document.
Assuming that we have an approximate transcription of the audio document and huge text corpus extracted from internet, several methodologies could be studied:
The proposed approaches will be validated using the ASR developed in our team.
Keywords: deep neural networks, automatic speech recognition, lexicon, out-of-vocabulary words.
- Bibliography [Mikolov2013] Mikolov, T., Chen, K., Corrado, G. and Dean, J. ?Efficient estimation of word representations in vector space?, Workshop at ICLR, 2013. [Deng2013] Deng, L., Li, J., Huang, J.-T., Yao, K., Yu, D., Seide, F., Seltzer, M., Zweig, G., He, X., Williams, J., Gong, Y. and Acero A. ?Recent advances in deep learning for speech research at Microsoft?, Proceedings of ICASSP, 2013. [Sheikh2016] Sheihk, I., Illina, I., Fohr, D., Linarès, G. ?Improved Neural Bag-of-Words Model to Retrieve Out-of-Vocabulary Words in Speech Recognition?. Interspeech, 2016. [Li2017] J. Li, G. Ye, R. Zhao, J. Droppo, Y. Gong , ?Acoustic-to-Word Model without OOV?, ASRU, 2017.
- Skills and profile: PhD in computer science, background in statistics, natural language processing, experience with deep learning tools (keras, kaldi, etc.) and computer program skills (Perl, Python). - Additional information:
Supervision and contact: Irina Illina, LORIA/INRIA (illina@loria.fr), Dominique Fohr INRIA/LORIA (dominique.fohr@loria.fr) https://members.loria.fr/IIllina/, https://members.loria.fr/DFohr/
Additional links : Ecole Doctorale IAEM Lorraine
Deadline to apply: June 6th Selection results: end of June
Duration :12 of months. Starting date: between Nov. 1st 2018 and Jan. 1st 2019
The candidates must have defended their PhD later than Sept. 1st 2016 and before the end of 2018. The candidates are required to provide the following documents in a single pdf or ZIP file:
In addition, at least one recommendation letter from the PhD advisor should be sent directly by their author(s) to the prospective postdoc advisor.
Help and benefits:
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6-25 | (2018-01-27) PhD grant Natural language processing: adding new words to a speech recognition system using Deep Neural Networks, INRIA/LORIA, Nancy, France Natural language processing: adding new words to a speech recognition system using Deep Neural Networks
- Location: INRIA/LORIA Nancy Grand Est research center France
- Research theme:Perception, Cognition, Interaction
- Project-team: Multispeech
- Scientific Context:
Voice is seen as the next big field for computer interaction. The research company Gartner reckons that by 2018, 30% of all interactions with devices will be voice-based: people can speak up to four times faster than they can type, and the technology behind voice interaction is improving all the time. As of October 2017, Amazon Echo is present in about 4% of American households. Voice assistants are proliferating in smartphones too: Apple?s Siri handles over 2 billion commands a week, and 20% of Google searches on Android-powered handsets in America are done by voice input. The proper nouns (PNs) play a particular role: they are often important to understand a message and can vary enormously. For example, a voice assistant should know the names of all your friends; a search engine should know the names of all famous people and places, names of museums, etc. An automatic speech recognition system uses a lexicon containing the most frequent words of the language and only the words of the lexicon can be recognized by the system. It is impossible to add all possible proper names because there are millions proper names and new ones appear every day. A competitive solution is to dynamically add new PNs into the ASR system. The idea is to add only relevant proper names: for instance if we want to transcribe a video document about football results, we should add the names of famous football players and not politicians. In this study, we will focus on the problem of proper names in automatic recognition systems. The problem is to find relevant proper names for the audio document we want to transcribe. To select the relevant proper names, we propose to use an artificial neural network.
- Missions:
We assume that in an audio document to transcribe we have missing proper names, i.e. proper names that are pronounced in the audio document but that are not in the lexicon of the automatic speech recognition system; these proper names cannot be recognized (out-of-vocabulary proper names, OOV PNs) The goal of this PhDThesis is to find a list of relevant OOV PNs that correspond to an audio document and to integrate them in the speech recognition system. We will use a Deep neural network to find relevant OOV PNs The input of the DNN will be the approximate transcription of the audio document and the output will be the list of relevant OOV PNs with their probabilities. The retrieved proper names will be added to the lexicon and a new recognition of the audio document will be performed.
During the thesis, the student will investigate methodologies based on deep neural networks [Deng2013]. The candidate will study different structures of DNN and different representation of documents [Mikolov2013]. The student will validate the proposed approaches using the automatic transcription system of radio broadcast developed in our team.
- Bibliography:
[Mikolov2013] Mikolov, T., Chen, K., Corrado, G. and Dean, J. ?Efficient estimation of word representations in vector space?, Workshop at ICLR, 2013.
[Deng2013] Deng, L., Li, J., Huang, J.-T., Yao, K., Yu, D., Seide, F., Seltzer, M., Zweig, G., He, X., Williams, J., Gong, Y. and Acero A. ?Recent advances in deep learning for speech research at Microsoft?, Proceedings of ICASSP, 2013.
[Sheikh2016] Sheihk, I., Illina, I., Fohr, D., Linarès, G. ?Improved Neural Bag-of-Words Model to Retrieve Out-of-Vocabulary Words in Speech Recognition?. Interspeech, 2016.
- Skills and profile: Master in computer science, background in statistics, natural language processing, experience with deep learning tools (keras, kaldi, etc.) and computer program skills (Perl, Python). - Additional information:
Supervision and contact: Irina Illina, LORIA/INRIA (illina@loria.fr), Dominique Fohr INRIA/LORIA (dominique.fohr@loria.fr) https://members.loria.fr/IIllina/, https://members.loria.fr/DFohr/ Additional links: Ecole Doctorale IAEM Lorraine
Duration: 3 years Starting date: between Oct. 1st 2018 and Jan. 1st 2019
Deadline to apply : May 1st 2018
The candidates are required to provide the following documents in a single pdf or ZIP file:
In addition, one recommendation letter from the person who supervises(d) the Master thesis (or research project or internship) should be sent directly by his/her author to the prospective PhD advisor.
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6-26 | (2018/02/01) Junior Linguist (French), Paris, France Junior Linguist [French]
Job Title:Junior Linguist [French] Linguistic Field(s):Phonetics, Phonology, Morphology, Semantics, Syntax, Lexicography, NLP Location:Paris, France Job description:The role of the Junior Linguist is to annotate and review linguistic data in French. The Junior Linguist will also contribute to a number of other tasks to improve natural language processing. The tasks include:
Minimum Requirements:
Desired Skills:
CV + motivation letter : maroussia.houimli@adeccooutsourcing.fr
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6-27 | (2018-02-16) Postdoctoral Research Scientist: Computational Linguistics, Rochester, NY, USA Postdoctoral Research Scientist: Computational Linguistics We invite applications for an interdisciplinary postdoctoral position with specialization in computational linguistics and/or technical or scientific methods in language science at Rochester Institute of Technology (RIT), in Rochester, NY. This is a one-year position with opportunity for renewal. The applicant should demonstrate a fit with our commitment to collaborate with colleagues across the university on research initiatives in Personalized Healthcare Technology. In addition to engaging in research projects, the right candidate will be able to teach a total of two courses per year - one course each in the College of Liberal Arts and the Golisano College of Computing and Information Sciences at RIT. The teaching assignment may be Computer Science Principles, Introduction to Language Science, Language Technology, Introduction to Natural Language Processing, Science and Analytics of Speech (acoustic and experimental phonetics), Spoken Language Processing (automatic speech recognition and text-to-speech synthesis), Seminar in Computational Linguistics, or another course depending on background.
Required Minimum Qualifications - PhD., with training in Computational Linguistics, Linguistics, or an allied field - Advanced graduate coursework in computational linguistics (natural language processing or speech processing), linguistics, or language science broadly - Publication record and plan for research and grant seeking activities - Ability to contribute in meaningful ways to our commitment to cultural diversity, pluralism, and individual differences
Required Application Documents Cover Letter, Curriculum Vitae or Resume, List of References, Research Statement
How To Apply Please apply at: http://careers.rit.edu/staff. Click the link for search openings and in the keyword search field, enter the title of the position or 3599BR.
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6-28 | (2018-02-18) Postdoctoral Research Associate (PDRA) at University of Kent, UK
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6-29 | (2018-02-19)Ph D at Loria/Inria and Telecom Paris Rech Nous proposons un sujet de thèse de doctorat sur le rehaussement de la parole par apprentissage profond au Loria/Inria Nancy Grand-EST et au LTCI/Télécom ParisTech.
Pour plus d'informations et pour pour postuler : https://team.inria.fr/multispeech/fr/phd-position-deep-learning-based-speech-enhancement-with-ad-hoc-microphone-arrays/
Clôture de l'appel à candidature le 30 avril 2018.
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6-30 | (2018-02-19) Post-Doctoral Researcher at Paderborn University, Germany
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6-31 | (2018-02-20) 1 (W/M) researcher positions at IRCAM, Paris, France
Deadline for application: March, 15th, 2018
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6-32 | (2018-02-22) Postdoctoral Researcher at Saarland University, GermanyPostdoctoral Researcher(computational linguistics or computer science) Models of Intercomprehension in Speech and LanguageThe Language Science and Technology department at Saarland University seeks to fill a postdoctoral position. Applications are invited from individuals with research expertise in any field related to speech science and speech technology. Our research project is concerned with the analysis of cross-lingual mutual intelligibility between Slavic languages. It studies the auditory-perceptual intercomprehension of Slavic languages based on analyses of the acoustic, phonetic and phonological structure of spoken utterances. This line of investigation will be complemented by using adaptation techniques established in speech synthesis and recognition to measure the distance between languages. In addition, similarity will be determined on the level of complete utterances.
The postdoc will join a vibrant community of speech and language researchers at Saarland University whose expertise spans areas such as computational linguistics, psycholinguistics, language and speech technology, speech science, theoretical and corpus linguistics, computer science, and psychology.
Requirements: The successful candidate should have a Ph.D./Master's in Computer Science, Computational Linguistics, or a related discipline, with a strong background in speech science and speech technology, in particular TTS and ASR. Strong programming skills are essential. A good command of English is mandatory. Working knowledge of German is desirable but not a prerequisite. Candidates must have completed their Ph.D. by the time of the appointment.
The position is a full position (100%) on the German E13 scale and subject to the final approval by the funding agency. Starting dates can be between July and October, 2018. The appointment will be for between one and four years.
About the department: The department of Language Science and Technology is one of the leading departments in the speech and language area in Europe. The flagship project at the moment is the CRC on Information Density and Linguistic Encoding. Furthermore, the department is involved in the cluster of excellence Multimodal Computing and Interaction. It also runs a significant number of European and nationally funded projects. In total it has seven faculty and around 50 postdoctoral researchers and PhD students.
How to apply: Please send us: (1) a letter of motivation, (2) your CV, (3) your transcripts, (4) a list of publications, and (5) the names and contact information of at least two references, as a single PDF or a link to a PDF if the file size is more than 3 MB.
Please apply by April 3rd, 2018.
Contacts: If you are interested in the project, please send an email to Bernd Möbius (moebius@coli.uni-saarland.de) and Dietrich Klakow (dietrich.klakow@lsv.uni-saarland.de).
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6-33 | (2018-03-02) POSTDOCTORAL FELLOW POSITION, CNRS and INSERM, Lyon, France POSTDOCTORAL FELLOW POSITION
Applications are invited for a 12-month full-time (with possible 12-month extension) Postdoctoral Position in cognitive neuroscience in Lyon, to collect and analyze fMRI data on language processing. The post-doc is part of an exciting new project, which is a collaboration between Drs Alice Roy and Véronique Boulenger from the Laboratory Dynamics of Language (CNRS), and Dr Claudio Brozzoli from the Lyon Neuroscience Research Centre (INSERM).
The project lies in the context of embodied cognition theories and aims at uncovering the functional role of the motor system in second language processing. It will examine, using fMRI, the dynamics of cortical activation in motor regions before and after phonological training in a foreign language. The project will be conducted in Lyon, a vibrant and stimulating neuroscience environment and a culturally rich city life, ideally located just an hour away from the Alpes, 2 hours from Paris and an hour and a half from Marseille and the Mediterranean sea (by train).
Key requirements for the candidates: The ideal candidate will have a PhD in neuroscience, cognitive sciences or a related field and will have substantial experience in fMRI imaging analyses (e.g. SPM, connectivity analysis, resting state) and good programming skills (MATLAB). A background in speech and language is required.
Applications in the form of a cover letter with statement of research interests and a CV with full publication list should be sent by email to alice.roy@cnrs.fr and veronique.boulenger@cnrs.fr, with cc to claudio.brozzoli@inserm.fr.
Applicants from outside the European Union are welcome but they must qualify for a valid visa. French speaking is not a requirement (although it is an asset) as long as the English language is mastered. Starting date: 2018 ? please contact us for further information. Net salary: ~2000 ? / month Applications will be considered until the position is filled.
Please feel free to forward this announcement to colleagues and students who could be interested in this position. http://www.ddl.ish-lyon.cnrs.fr/equipes/index.asp?Langue=EN&Equipe=7&Page=Presentation&
-- Véronique Boulenger Chargée de Recherche CNRS Laboratoire Dynamique Du Langage UMR5596 CNRS/Université de Lyon 04.72.72.79.24 veronique.boulenger@cnrs.fr
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6-34 | (2018-03-03) Maitre de conférences, ENSIMAG, Grenoble,France Ecole de rattachement : ENSIMAG
Site web de l?école : http://ensimag.grenoble-inp.fr/
Contact de l?école : Jean-Louis.Roch@grenoble-inp.fr, Olivier.Francois@grenoble-inp.fr
Profil d?enseignement :
L?Ensimag recrute un maître de conférences en mathématiques appliquées ou en informatique
afin de développer les enseignements d?apprentissage statistique, d?intelligence artificielle, de
visualisation de données, de calcul haute performance ou de « big data ». Le dossier de
candidature devra faire apparaître le caractère ?interdisciplinaire? du candidat, sa capacité à
prendre des responsabilités au sein de la structure, ainsi qu?une liste conséquente de travaux
ou publications en relation avec une ou plusieurs branches de la science des données. Outre la
formation aux sciences des données (synthèse de programmes à partir de données, aide à la
décision), la personne recrutée devra s?investir dans les enseignements du tronc commun
Ensimag (1ère année et environ 75% des filières de la 2ème année) qui constitue le socle de nos
élèves ingénieurs. Elle sera amenée à s'investir et prendre des responsabilités dans des
parcours de l?Ecole tels que le « mastère big data » ou le master « Data Science ». En
partenariat avec des industriels, la personne recrutée pourrait superviser l?organisation de «
challenges » et de « hackatons » afin d?enrichir les contacts de l?Ecole dans le domaine de
l?intelligence artificielle et des « big data ». En collaboration avec les équipes pédagogiques
concernées, elle devra s?impliquer dans le montage d?enseignements par projets et la
formation par le Numérique.
RECHERCHE
Laboratoire d?accueil : LIG / LJK
Site web du laboratoire : http://www.liglab.fr/
Contact du laboratoire : Eric Gaussier (eric.gaussier@imag.fr), LIG
Stéphane Labbé (stephane.labbe@imag.fr), LJK
Profil de recherche :
Le candidat effectuera ses recherches dans le domaine de l?intelligence artificielle ou de la
science des données, et montrera son ouverture aux différentes approches possibles dans ce
domaine. Les thématiques privilégiées sont l?apprentissage sur données complexes, structurées
ou non structurées, l?apprentissage profond et les réseaux de neurones et en particulier les
problématiques d?optimisation, de causalité, de capacité de généralisation et leur analyse
mathématique. Parmi les applications de l?apprentissage et de l?apprentissage profond, un
intérêt particulier est porté au traitement du signal et de l?image, à l?apprentissage de
représentation, à l?apprentissage avec des données multimédia, des données langagières pour
des problématiques issues du traitement du langage naturel, les thématiques de transparence
des mécanismes d?apprentissage, ainsi que les applications en biologie, santé, sciences
humaines, réseaux sociaux, physique, environnement, etc.
Le recrutement renforcera les liens entre le LIG et le LJK dans les domaines de la science des
données et de l?apprentissage automatique. Les deux laboratoires sont localisés sur le campus
de Saint Martin d?Hères et ont des collaborations actives, en particulier au sein de l?axe du
traitement de données et de connaissance à large échelle (équipes AMA, GETALP, MRIM,
SLIDE), des équipes PERVASIVE, TYREX du LIG et au sein du département Proba-Stat (équipes
DAO, SVH, MISTIS, FIGAL) et de l?équipe THOTH du LJK. Parmi les projets communs entre les
deux laboratoires, on peut également citer les problèmes de prédiction et de classification avec
des données structurées de type fonctionnelles, le transport optimal pour l?apprentissage, les
problèmes de parcimonie et de régularisation pour l?apprentissage multitâches et leur
résolution par des méthodes d?optimisation stochastique. La personne recrutée montrera sa
capacité à jouer un rôle actif dans les projets contractuels académiques (ANR, FUI, PFIA, EU...)
et industriels sur ces thèmes très porteurs.
ACTIVITES ADMINISTRATIVES
Spécificités du poste ou contraintes particulières :
Activités administratives liées aux fonctions de maître de conférences : responsabilités d?unité
d?enseignement, responsabilités de filières ou d?année.
Compétences attendues :
Savoir : Enseignement de l?informatique, de l?intelligence artificielle et de la science
des données
Savoir-faire : Pédagogie et responsabilités dans l?Ecole
Savoir-être : Travail en équipe
pdf
Intelligence artificielle, Science des données, Big data, Apprentissage
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6-35 | (2018-03-03) Research Linguist at ObEN, Los Angeles,CA, USA RESEARCH LINGUIST ● Design material and procedures to collect spoken and written language data; ● Design schemas and label/tag sets to annotate recordings and text with phonetic, prosodic, semantic, and syntactic features; ● Design methods and protocols to ensure the quality of linguistic data and annotations; ● Design perceptual or linguistic tests to evaluate the performance of speech and language systems; ● Contribute to the formalization of speech and language models by offering linguistic knowledge, identifying issues and providing solutions. ● Masters or higher degree in Linguistics or a closely-related field ● Specialization in Phonetics or Phonology ● Native or near-native proficiency in Japanese or Korean ● Ability to use programming scripts ● Knowledge of scripting languages, e.g., Python ● Background in Psychology/Psycholinguistics ● Willingness to accept reprioritization as necessary
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6-36 | (2018-03-03) Speech Research Scientist (ASR) at ObEN, Los Angeles, CA, USA SPEECH RESEARCH SCIENTIST (ASR) ● Develop long (>1h) speech-text alignment systems; ● Develop lyrics-singing voice alignment systems; ● Develop tools and measures for data selection (confidence scores, acoustic measures); ● Develop tools for metadata extraction from speech and text (e.g: emotion, speakerID, etc). ● PhD with strong research experience in ASR demonstrated by publications in top Speech Journals and Conferences (ICASSP, Interspeech, ASRU, etc.); ● Experience with robust ASR, long speech-text alignment, lightly supervised approaches and confidence measures computation; ● Fluent in Python and C++, excellent knowledge of Kaldi; ● Strong machine learning background and familiar with standard statistical modeling techniques applied to speech; ● Good knowledge of deep learning packages (Tensorflow, Theano, Keras, etc).
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6-37 | (2018-03-03) Speech Research Scientist (Prosody Modeling) at ObEN, Los Angeles, CA, USA SPEECH RESEARCH SCIENTIST (Prosody Modeling) ● Develop new prosody model for different languages, adaptable using a small amount of data; ● Develop generic prosodic models for different expressivity which can be applied to any voice; ● Develop sentiment analysis algorithms to control expressivity from text input. Requirements: ● PhD with strong experience in Prosody Modeling for Speech Synthesis demonstrated by publications in top Speech Journals and Conferences (Speech prosody, Icassp, Interspeech, etc); ● Strong implementation skills and general knowledge in ML; ● Fluent in Python and C++, and good knowledge of deep learning packages; ● Familiarity with linguistic phonetics; ● Knowledge of basic digital signal processing techniques for audio.
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6-38 | (2018-03-03) Speech Research Scientist (Singing Voice Synthesis) at ObEN, Los Angeles, CA, USA SPEECH RESEARCH SCIENTIST (Singing Voice Synthesis) ● Develop and improve ObEN’s virtual singing voice technology based on novel voice model with improved glottal source modelingl; ● Explore new approaches for singing voice generation based on deep generative models; ● Develop singing voice generation approach from musical annotation. ● PhD with strong experience in speech synthesis, preferably singing voice synthesis demonstrated by publications in top Speech journals and conferences (Icassp, Interspeech, etc); ● Good experience in deep generative models and sequential modelling; ● Strong implementation skills and knowledge in ML; ● Fluent in Python and C++, and good knowledge of deep learning packages; ● Familiarity with linguistic phonetics; ● Knowledge of basic digital signal processing techniques for audio.
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6-39 | (2018-03-03) Speech Research Scientist (Speech Synthesis) at ObEN, Los Angeles, CA, USA SPEECH RESEARCH SCIENTIST (Speech Synthesis) ● Develop and extend ObEN’s glottal source model, in view of improving the quality, flexibility and control (e.g. voice quality, expressivity) of ObEN’s speech and singing voice synthesis system; ● Develop new speech generation approaches based on deep generative models (e.g. wavenet) with reduced amount of data and better control. ● PhD with strong experience in Speech Synthesis demonstrated by publications in top Speech Journals and Conferences (Icassp, Interspeech, etc); ● Expertise in signal processing in particular in the design of voice models (glottal source model, ...) allowing a fine control of the characteristics of the synthesized voice (speech and singing voice); ● Experience in deep generative model of raw audio (wavenet) and Generative Adversarial Network (WGAN); ● Fluent in Python and C++, and good knowledge of deep learning packages (TensorFlow, Theano, Keras, etc); ● Familiarity with linguistic phonetics; ● Knowledge of basic digital signal processing techniques for audio.
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6-40 | (2018-03-03) Speech Research Scientist (TTS) at ObEN, Los Angeles, CA, USA SPEECH RESEARCH SCIENTIST (TTS) ● Develop deep generative model of raw speech waveform; ● Develop cross-lingual approaches (e.g. phonetic posteriorgrams). ● PhD with strong research experience in Adaptation of DNN-based TTS systems demonstrated by publications in top Speech journals and conferences (Icassp, Interspeech, etc); ● Strong machine learning background and familiar with standard statistical modeling techniques applied to speech; ● Research experience in deep generative model of raw audio (wavenet) and Generative Adversarial Network (WGAN); ● Fluent in Python and C++, and expert knowledge of deep learning packages (TensorFlow, Theano, Keras, etc); ● Familiarity with linguistic phonetics; ● Knowledge of basic digital signal processing techniques for audio.
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6-41 | (2018-03-06) Post Doc position at University of Saarland, Germany Post Doc position (computer science, computational linguistics, physics or similar)
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6-42 | (2018-03-14) PhD Position in Experimental Mechanics of Materials/Structures (vocal-fold 3D structure), Gipsa Lab, Grenoble PhD Position in Experimental Mechanics of Materials/Structures
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6-43 | (2018-03-15) Internship at ELDA, Paris, France Nous recherchons un-e stagiaire dans le cadre d'un projet ayant pour but l'actualisation
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6-44 | (2018-03-19) Faculty position (Associate professor) at Telecom ParisTech, Paris Telecom ParisTech has one new permanent (indefinite tenure) faculty position (Associate Professor) in machine learning. Applicants from machine learning for speech processing, natural language processing or affective computing are welcomed. More information on the social computing topic is avalable here : https://www.tsi.telecom-paristech.fr/en/research/1885-2/social-computing-topic/
******************************************************** Faculty position (Associate professor) at Telecom ParisTech in Machine-Learning.
Important Dates ? May 25th, 2018: closing date ? Mid June: hearings of preselected candidates
Telecom ParisTech?s [1] machine learning, statistics and signal processing group (a.k.a S²A group) [2], within the laboratoire de traitement et communication de l?information (LTCI) [5], is inviting applications for a permanent (indefinite tenure) faculty position at the *Associate Professor* level (Maitre de Conferences) in *Machine learning*.
Main missions
The recruit will be expected to:
Research activities ? Develop groundbreaking research in the field of theoretical or applied machine learning, targeting applications that are well aligned with the topics of the S²A group [3] and the Images, Data & Signals department [4], which include (and is not restricted to) time series analysis (audio, ?), reinforcement learning, natural language processing, social signal processing, predictive maintenance, biomedical or physiological signal analysis, recommendation, finance, health, ?. ? Develop both academic and industrial collaborations on the same topic, including collaborative activities with other Telecom ParisTech research departments and teams, and research contracts with industrial players ? Set up research grants and take part in national and international collaborative research projects
Teaching activities ? Participate in teaching activities at Telecom ParisTech and its partner academic institutions (as part of joint Master programs), especially in machine learning and Data science, including life-long training programs (e.g. the local Data Scientist certificate)
Impact ? Publish high quality research work in leading journals and conferences ? Be an active member of the research community (serving in scientific committees and boards, organizing seminars, workshops, special sessions...)
Candidate profile
As a minimum requirement, the successful candidate will have:
? A PhD degree ? A track record of research and publication in one or more of the following areas: machine learning, applied mathematics, signal processing, ? Experience in teaching ? Good command of English
The ideal candidate will also (optionally) have: ? Experience in temporal data analysis problems (sequence prediction, multivariate time series, probabilistic graphical models, recurrent neural networks...)
NOTE: The candidate does *not* need to speak French to apply, just to be willing to learn the language (teaching will be mostly given in English)
Other skills expected include: ? Capacity to work in a team and develop good relationships with colleagues and peers ? Good writing and pedagogical skills
More about the position ? Place of work: Paris until 2019, then Saclay (Paris outskirts) ? For more information about being an Associate Professor at Telecom ParisTech, check [6] (in French)
How to apply Applications are to be sent by e-mail to: recrutement@telecom-paristech.fr
The application should include: ? A complete and detailed curriculum vitae ? A letter of motivation ? A document detailing past activities of the candidate in teaching and research: the two types of activities will be described with the same level of detail and rigor. ? The texts of the main publications ? The names and addresses of two referees ? A short teaching project and a research project (maximum 3 pages)
Contacts : Slim Essid (Coordinator of the ADASP team) Florence d?Alché-Buc (Professor, Machine Learning) Stéphan Clémençon (Head of the S²A group) Gaël Richard (Head of the IDS department)
[1] http://www.tsi.telecom-paristech.fr [2] http://www.tsi.telecom-paristech.fr/ssa/ [3] http://www.tsi.telecom-paristech.fr/aao/en/
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6-45 | (2018-03-24) PhD-student in a research project investigating strategies for human?robot-interaction, Bielefeld, Germany The Social Cognitive Systems group (headed by Prof. Dr. Stefan Kopp; Cluster of Excellence Cognitive Interaction Technology, Bielefeld University, Germany) is currently looking for a PhD-student in a research project investigating strategies for human?robot-interaction, with a focus on generation of multimodal spoken dialogue behaviour.
Applicants should have a masters degree in computer science or (computational) linguistics with a focus on machine learning, statistical methods in natural language processing, and/or dialogue modelling and should have strong communication skills and be motivated to work in an interdisciplinary team of computer scientists, psychologists, engineers, and designers.
The position is fully paid (TV-L 13) with funding for three years. The official job advertisement (in German) can be found here: https://scs.techfak.uni-bielefeld.de/scswp/wordpress/wp-content/uploads/2018/03/wiss18072.pdf The deadline for applications to receive full consideration is 2018-04-06.
If you have any questions or want to know more about the research project, our research group, or living and working in Bielefeld, don't hesitate to contact Stefan Kopp <skopp@techfak.uni-bielefeld.de>.
-- Hendrik Buschmeier Social Cognitive Systems Group, CITEC, Bielefeld University
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6-46 | (2018-03-26) PhD grant in Machine learning, Lannion, France L?équipe Expression de l?IRISA propose une thèse en Informatique co-financée par la DGA sur le sujet suivant « Machine learning models for multimodal detection of anomalous behaviors ».
La description du sujet est disponible à cet emplacement :
Profil des candidats : Les candidat(e)s doivent être titulaire d'un Master recherche en informatique. Ils doivent également posséder un bon niveau de développement (C/C++/Python/?) ainsi que des connaissances en apprentissage automatique et si possible en traitement du signal. La DGA impose que les candidats posséder la nationalité d?un pays membre de l?Europe. Un excellent niveau en anglais est requis.
Date limite de candidature : 10 avril 2018
Localisation : Lannion
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6-47 | (2018-03-15) PhD grant at LJK and LIG, Grenoble, France CDP TITLE: Performance Laboratory
SUBJECT TITLE: Computational Video Editing for Stage Performances
SCIENTIFIC DEPARTMENT (LABORATORY’S NAME): LJK+LIG
DOCTORAL SCHOOL’S: MSTII (Mathématiques appliquées et informatique)
SUPPORTER’S NAME: Rémi Ronfard & Benjamin Lecouteux
The PERFORMANCE LABORATORY cross-fertilises UGA’s performing arts, geography-urban studies
and computer science communities to produce innovative performance as research. This new
interdisciplinary community of 41 academics will allow the development of cutting edge art research, digital
documentation, performance literacy tools and innovative forms of material and immaterial heritage. This
will push the very boundaries of the scientific disciplines themselves, both methodologically and
epistemologically, and in turn, create a new pluridisciplinary ecosystem at CUGA.
SUBJECT DESCRIPTION:
Context : This PhD thesis is proposed as part of an ongoing collaboration between computer scientists and
performings arts researchers at Univ. Grenoble Alpes and INRIA to use video in teaching and researching
the performing arts. In a previous project, the IMAGINE team at LJK and INRIA developped methods for
automatic generation of cinematic rushes from ultra high definition video recordings of stage performances
[1]. Here, we would like to propose techniques for making documentary movies from the generated rushes,
based on an analysis of the script of the performance and a formalization of the rules of film editing. Ideally,
the proposed techniques should be completely non-invasive (not requiring sensors on actors or on stage)
and intuitive enough to be used by performing arts students, professors and researchers, without any
expertise in video production.
Description: The goal of the PhD thesis will be to propose novel interaction techniques to students,
professors and researchers in the performing arts for making movies from stage performances recorded on
stage. On the one hand, we will propose novel algorithms for editing cinematographic rushes together into
movie clips automatically, based on computational models of film editing « idioms » and machine analysis
of the actors speech and motion. On the other hand, we will propose novel user interfaces for easily
choosing between available idioms as in [2] and creating new idioms for the specific purpose of teaching
and researching mise en scene and acting techniques.
During his/her thesis, the PhD student will create an extensive database of stage performance recordings,
as part of a collaboration with the performing arts department at Univ. Grenoble Alpes and associated
theatre companies. The raw recordings and the generated movies will be used as supporting material for
teaching mise- en-scène and acting techniques, and for researching multiple aspects of expressive human
motion, verbal and non-verbal communication, and dramaturgic techniques, as part of the new crossdisciplinary
research project « Performance Lab ».
References:
[1] Vineet Gandhi, Rémi Ronfard, Michael Gleicher. Multi-Clip Video Editing from a Single Viewpoint.
CVMP 2014 - European Conference on Visual Media Production, Nov 2014.
[2] Mackenzie Leake, Abe Davis, Anh Truong, and Maneesh Agrawala. Computational video editing for
dialogue-driven scenes. ACM Trans. Graph. 36, 4, July 2017.
ELIGIBILITY CRITERIA
Applicants:
- must hold a Master's degree (or be about to earn one) or have a university degree equivalent to a
European Master's (5-year duration),
Applicants will have to send an application letter in English and attach:
- Their last diploma
- Their CV
- A short presentation of their scientific project (2 to 3 pages max)
- Letters of recommendation are welcome.
Address to send their application: remi.ronfard@inria.fr, benjamin.lecouteux@univ-grenoble-alpes.fr
SELECTION PROCESS
Application deadline: May 15th 2018 at 17:00 (CET)
Applications will be evaluated through a three-step process:
1. Eligibility check of applications in May 17th 2018
2. 1st round of selection: the applications will be evaluated by a Review Board and results will be May
25th.
3. 2nd round of selection: shortlisted candidates will be invited for an interview session in Grenoble on
May 31st 2018 (if necessary).
4. Final decision will be given June 30.
TYPE of CONTRACT: temporary-3 years of doctoral contract
JOB STATUS: Full time
HOURS PER WEEK: 35
OFFER STARTING DATE: October 1 2018
APPLICATION DEADLINE: May 15th 2018
Salary: between 1768.55 € and 2100 € (gross) per month (depending on complementary activity or not)
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6-48 | (2018-03-16) Research Linguist at ObEN, Inc, Pasadena, California, USA RESEARCH LINGUIST
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6-49 | (2018-03-16) SPEECH RESEARCH SCIENTIST (ASR) at ObEN, Inc, Pasadena, California,USA SPEECH RESEARCH SCIENTIST (ASR)
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6-50 | (2018-03-16) SPEECH RESEARCH SCIENTIST (Prosody Modeling)at ObEN Inc.,Pasadena, California, USA SPEECH RESEARCH SCIENTIST (Prosody Modeling)
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6-51 | (2018-03-16) SPEECH RESEARCH SCIENTIST (Singing Voice Synthesis) at ObEN Inc., Pasadena, California, USA SPEECH RESEARCH SCIENTIST (Singing Voice Synthesis)
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6-52 | (2018-03-16) SPEECH RESEARCH SCIENTIST (Speech Synthesis) at ObEN Inc., Pasadena, California, USA SPEECH RESEARCH SCIENTIST (Speech Synthesis)
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6-53 | (2018-03-16) SPEECH RESEARCH SCIENTIST (TTS) at ObEN Inc., Pasadena, California, USA SPEECH RESEARCH SCIENTIST (TTS)
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6-54 | (2018-03-17) 2 PhD grants and 2 postdoc positions (2-year), at Aix-Marseille/Avignon , France
2 PhD grants and 2 postdoc positions (2-year)at Aix-Marseille/Avignonon Language, Communication and the BrainThe Center of Excellence on Brain and Language (BLRI, www.blri.fr/) and the Institute of Language, Communication and the Brain (ILCB, http://www.ilcb.fr/ ) award :
The BLRI-ILCB is located in Aix-en-Provence, Avignon and Marseille and regroups several research centers in linguistics, psychology, cognitive neuroscience, medicine, computer science, and mathematics. . PhD grants : Monthly salary: 1 685? (1 368? net) for a period of 3 years . Postdoc: Monthly salary: ~2000 ? net (depending on experience) . Deadline: June 17, 2018 HOW TO APPLY Candidates should first contact potential supervisor(s) among the members of the ILCB/BLRI. A list of potential projects and supervisors that will be given priority for this call can be find here. However, you can also apply to any subject, under the supervision of any ILCB/BLRI member (http://www.blri.fr/members.html.). When the research project is finalized and approved by the supervisor(s), the application must be sent to nadera.bureau@blri.fr.
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6-55 | (2018-03-22) Research scientist at the University of Trento, Italy At the University of Trento ( Italy ) we are looking for highly motivated researcher to join our research team and work on Natural Language Understanding and Dialog Modeling and Systems. The Signals and Interactive Systems Lab at University of Trento attracts researchers from computational linguistics, computer science, electrical engineering to design and train the most advanced interactive and conversational systems. You will join the research team that has been training intelligent machines and evaluating AI-based systems for more than two decades, collaborating with leading research labs and successful startups in the world. You can check a sample of the projects in the area of Natural Language Understanding, Conversational Systems and Personal Agents ( and more ) at: http://sisl.disi.unitn.it/demo/ The candidates should have strong background, past achievement records in at least in one of the following areas: - Natural Language Understanding - Conversational Modeling and Systems - Machine Learning For more info on research and projects visit the lab website Visit lab website at http://sisl.disi.unitn.it/ The official language (research and graduate teaching) of the department is English. FELLOWSHIP The research fellowship will depend on experience and in the range of 19367 - 33000 Euros per year. The position is for one year, renewable. For more information about cost of living, campus, please visit the graduate school website at http://ict.unitn.it/ DEADLINES Immediate openings with start date as early as May 2018. Open until filled. REQUIREMENTS - PhD degree in Computer Science, Computational Linguistics, Machine Learning or similar or affine disciplines. - Strong academic record (publications in top conferences and journals) - Strong programming skills - Excellent command of oral and written English - Excellent understanding of experimental design methodology and statistics - Excellent understanding of natural language processing - Excellent understanding of machine learning methods - Experience working on research projects - Excellent team-work skills - Supervison of students HOW TO APPLY Interested applicants should send their 1) CV 2) At least three reference letters sent to: Email: sisl-jobs@disi.unitn.it For more info: Signals and Interactive Systems Lab: http://sisl.disi.unitn.it/ PhD School : http://ict.unitn.it/ Department : http://disi.unitn.it/ Information Engineering and Computer Science Department (DISI) DISI has a strong focus on cross-disciplinarity with professors from different faculties of the University (Physical Science, Electrical Engineering, Economics, Social Science, Cognitive Science, Computer Science) with international background. DISI aims at exploiting the complementary experiences present in the various research areas in order to develop innovative methods, technologies and applications. University of Trento The University of Trento is consistently ranked as premiere Italian university institution. See http://www.unitn.it/en/node/1636/mid/2573 University of Trento is an equal opportunity employer.
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6-56 | (2018-04-09) Postes d'ATER en Traitement automatique des langues et de la Parole, Sorbonne Université, Paris, France Des postes d'ATER en Traitement automatique des langues et de la Parole sont disponibles à la faculté des lettres de Sorbonne Université. Le lien pour postuler est http://concours.univ-paris4.fr/PostesAter?entiteBean=posteCandidatureCourant
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6-57 | (2018-04-11) A three-year doctoral position at the University Sorbonne Nouvelle, Paris, France Dear colleagues, The Laboratory of Phonetics and Phonology (http://lpp.in2p3.fr/), Paris, France, offers a funded position for a PhD candidate for a period of three years on the acoustic phonetic markers of inter and intra-speaker variability with a special notice considering the normalization of procedures. We would be most grateful if you could also distribute this information among other persons who may be interested by this offer.
Descriptif de l?offre :
Offre de contrat doctoral par le Laboratoire de Phonétique et Phonologie : « Marqueurs phonétiques et acoustiques de la variabilité inter- et intra-individuelle »
Le Laboratoire de Phonétique et Phonologie propose un contrat doctoral de 3 ans financé par l?ANR pour la rentrée universitaire 2018. Le thème du doctorat proposé ici a pour objectif d'analyser les marqueurs phonétiques et acoustiques de la variabilité inter et intra locuteurs. Une attention particulière sera portée à la standardisation des méthodes d?analyse proposées, permettant leur transposition dans des domaines d?application connexes, dont celui du traitement automatique de la parole.
Il s?agira de prendre en compte des caractéristiques de la voix/parole très liées au contexte de la comparaison de voix. Dans la mesure où les variations de la parole sont multifactorielles, il apparaît indispensable d?établir des standards de mesures objectives pour lesquelles les méthodologies récentes de la phonétique expérimentale peuvent apporter une garantie. On s?intéressera notamment aux marqueurs acoustiques qui retranscrivent des propriétés physiologiques individuelles ainsi qu?aux habitudes articulatoires, vecteurs d?identité sociale.
Le/la doctorant(e) effectuera ses recherches au LPP (Laboratoire de Phonétique et de Phonologie), une unité de recherche mixte CNRS/Université Paris3 Sorbonne Paris Cité. Voir les travaux sur ce thème du Laboratoire de Phonétique et de Phonologie http://lpp.in2p3.fr Le/la candidat(e) sélectionné(e) sera encadré(e) par Cédric Gendrot et Cécile Fougeron, respectivement enseignant-chercheur de l?Université Sorbonne Nouvelle et Directrice de recherche au CNRS. Il/elle dépendra de l'Ecole Doctorale ED268 de l'Université Sorbonne nouvelle. Le/la doctorant(e) bénéficiera des ressources du laboratoire, de l'Ecole Doctorale ED268 et de l'environnement de recherche interdisciplinaire du Laboratoire d'Excellence EFL. Il/elle pourra assister à des séminaires hebdomadaires de recherche phonétique et phonologie au LPP et d'autres équipes de recherche, suivre des conférences données par des professeurs invités de stature internationale, des formations, des colloques et des écoles d'été.
? Conditions - avoir une bonne maitrise de la langue française. - avoir mené avec succès un premier projet de recherche personnel - aucune condition de nationalité n'est exigée. - avoir de très bonnes connaissances en traitement de données de type phonétique acoustique. - des connaissances en informatique et en analyse statistique seraient un plus.
? Pièces à joindre pour la candidature 1. un CV 2. une lettre de motivation 3. le mémoire de master 2 en phonétique 4. le nom de deux référents (avec leur adresse courriel)
Date limite de candidature: 30 juin 2018
Les dossiers complets seront à envoyer par mail au plus tard le 30 juin 2018 à Cédric Gendrot (cgendrot@univ-paris3.fr) et Cécile Fougeron (cecile.fougeron@univ-paris3.fr)
Les candidats présélectionnés seront auditionnés entre le 2 et le 6 juillet 2018) sur place ou par visio-conférence. Contact pour plus d?information : Cédric Gendrot : cgendrot@univ-paris3.fr Cécile Fougeron : cecile.fougeron@univ-paris3.fr
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