CNRS is recruiting 25 tenure-track positions



  • The CNRS is recruiting 25 tenure-track positions among which one is dedicated to Machine Learning for Natural Language Processing.


  • This contract provides a dedicated financial environment upon joining the CNRS, and includes teaching activities in a higher education institution.


  • These positions are offered on fixed-term contracts (CDD) under public law for a duration of 3 to 6 years.


  • Deadline for submitting the application : 31/08/2022


  • CNRS announcement : https://www.cnrs.fr/en/cnrsinfo/join-cnrs-25-tenure-track-positions-available


  • Offer on Machine Learning for Natural Language Processing https://emploi.cnrs.fr/Offres/CPJ/CPJ-2022-020/Default.aspx? Lang=EN


PhD position on the study of bias and methods to debias Deep Learning model



  • We are launching a call for applications for a PhD position on the study of bias and methods to debias Deep Learning models, or even make the compression process unbiased.


  • This thesis is part of the ANR DIKé project, which focuses on the study of bias in compressed Deep Learning models with an application to Natural Language Processing.


  • Abstract The objective of this project is to be able to identify if a compressed model is biased through the creation of measures to evaluate this bias. It will then identify the origins of this bias in the compression and establish new methods to compress complex deep models without favoring one class of objects/individuals over another for example.


  • Objective (in brief) The future PhD student will first have to carry out a bibliographical work to improve (if necessary) his/her knowledge in the field of NLP and in particular to master the architecture of the networks commonly used in such a field. He or she will then study the different compression techniques of Deep Learning models, such as pruning or distillation.


  • After this preliminary work, the recruited candidate will be able to provide a bibliographical work concerning the evaluation of biases in Machine Learning models. It will also be necessary to determine the origins of the bias in the said models. To do so, he/she will study the different metrics as well as the compression methods of Deep Learning models used in NLP on benchmarks found during the bibliographic work.


  • Several tracks are proposed to treat the problem according to the preliminary studies carried out on the data but also on the models: generation of data and to cure the bias present in the models one will be able to be interested in this task after compression by approaches based on the learning in an unbalanced context or on the fairness. The final objective is to be able to debiased the compression process itself.


  • You can find more information at the following address as well as the application form:


  • https://guillaumemetzler.github.io/documents/offers/phd_position_dike.pdf


INRAE offers a fixed-term contract at the Design Engineer level



  • The ANR D2KAB offers several offers of engineering fixed-term contracts during the duration of this project.


  • The position is funded by the Copain team of the TSCF laboratory of the INRAE Center of ARA Clermont. In the D2KAB research project, this team works in collaboration with the Bibliome team of the MaIAGE laboratory in the INRAE center of Jouy-en-Josas and the COMPUTER team of the MISTEA laboratory of the INRAE center in Montpellier. The final location will be determined according to the application. Occasional trips are to be expected between the centers of Jouy-en-Josas, Clermont-Ferrand and Montpellier.


  • The Research Unit Technologies and Information Systems for Agrosystems (TSCF), composed of 3 teams that bring together 60 agents, is located on 2 sites: the Scientific and University Pole of Cézeaux in Aubière (63) and the Montoldre Research and Experimentation Site (03). https://www6.ara.inrae.fr/tscf/


  • The activity of the Copain team is devoted to the engineering methods of communicating information systems dedicated to agri-environmental management . Copain's researchers specialize in computer science and information systems, with a solid experience in interdisciplinary projects. The activity of this team is dedicated to information systems engineering methods for agri-environmental management. These methods cover the needs of the actors, the definition of the characteristics of information systems, their modeling, their management.


  • The MaIAGE research unit brings together mathematicians , computer scientists, bioinformaticians and biologists around questions of biology and agro-ecology, ranging from the molecular scale to the landscape scale through the study of the individual, populations or ecosystems.


  • The unit develops original mathematical and computational methods of generic scope or motivated by specific biological problems. It is also involved in the provision of databases and software allowing biologists to use the tools in good conditions or to automatically exploit the scientific literature.


  • The research questions of the Bibliome team are the development and adaptation of methods of Information Extraction from Text (EI), Documentary Research, Automatic Language Processing (NLP) and Learning on Textual Data, in the service of biological research. The team's approach is to develop methods of automatic knowledge acquisition and software engineering to adapt language processing to areas of application through learning methods. It also develops all the processing chains necessary for the evaluation and exploitation of these methods.


  • Standard contract : fixed-term contract of design engineer.


  • Profile: holder of a Master 2 degree or engineer in computer science, bioinformatics, data-science, TAL.


  • Duration: 12 months renewable up to a total of 24 months.


  • Hiring start date: September 2022 (to be negotiated).


  • Location: an INRAE center, Jouy en Josas, Clermont or Montpellier.


  • Remuneration about 2033 € gross monthly, depends on the diploma and experience of the candidate.


  • Contact: Catherine Roussey, INRAE Centre de Clermont-Ferrand ([email protected])


  • Co-supervision by Robert Bossy, INRAE, Jouy-en-Josas ([email protected])


  • Application Send a CV and a cover letter to Catherine Roussey ( [email protected]).


  • The cover letter should show how your current skills fit the profile of this position. If possible, indicate a French referent who has worked with you.


  • Application deadline: December 2022.


  • Interviews are conducted over time, to take up the post as soon as possible.


  • For any request for information contact [email protected]


PhD student recruitment multi-agent simulation for decision support in the context of urban logistics



  • Scientific and technical skills o Modeling, Multi-Agent Simulation o Programming: Java and Python o Notions of supply chain management (optional) o Good writing skills in French and English


  • Interpersonal skills  Autonomy and curiosity  Teamwork  Rigour Miscellaneous information


  •  Location: Paris and Saint-Etienne (short stay to be defined)  Supervision: Arthur Gaudron, Gustavo Nardin, Flavien Balbo


  •  Application deadline: June 15, 2022


  •  Start: October 2022


  • Application file  CV  Cover letter  Master Transcripts  Letters of Recommendation  Justification of research experience (Master thesis, internship in a research laboratory)  Any other document room you deem useful


  • The application material should be addressed to [email protected], [email protected], [email protected]


CDD Engineer Web Developer full stack, Labex persyval Grenoble



  • You will find below a 12-month fixed-term job offer (possibility of extension) for a full stack Web developer engineer position at the University of Grenoble, as part of the Labex Persyval-lab.


  • • Type of employment: one-year full-time fixed-term contract (possibility of extension) • Location: Grenoble (Saint-Martin-d'Hères University Campus) • Level: Research Engineer (Bac +5) • Position to be filled immediately


  • Context The LabEx PERSYVAL-Lab (https://persyval-lab.org/), is recruiting a full stack Web Developer for its website, and its PerSciDo platform ( https://persyval-platform.univ-grenoble-alpes.fr) for referencing and sharing datasets.


  • Missions The engineer will provide and maintain the tools for the collaborative work environment and enhancement of the LabEx. In particular, he will be in charge of: - the redesign of the Labex website (https://persyval-lab.org/) and the "persyval-calls" web application (https://persyval-calls.imag.fr/fr/) which manages Persyval-lab's calls for projects, - the support and maintenance of the existing PerSCiDO platform for sharing research datasets ( https://perscido.univ-grenoble-alpes.fr/).


  • Profile sought • Drupal CMS expertise • Python expertise (Flask framework) • System expertise (Debian)


  • • Knowledge of PHP language (Symfony2 framework) • Desired experience in continuous integration (Gitlab, Docker) • Knowledge of Semantic Web technologies would be a plus.


  • Remuneration based on the remuneration grid of the contract staff management regulations: according to diploma and professional experience . From 23 k € to 36 k €


  • Contact: Send your curriculum vitae accompanied by a cover letter to Marie-Christine ROUSSET, PerSCiDO Mail Project Manager: [email protected] PeRSCiDO Team: [email protected]


IT contract teaching position offer - Polytech Nantes



  • Polytech Nantes is recruiting a full-time teacher to strengthen its teaching team in the engineering cycle (bac + 3/4/5) in computer science. With 230 students in the computer engineering cycle, it is a major player in training in Nantes in this field. Since the beginning of the 2021 academic year, this training course has also been open under apprentice status in the "Data Engineering and Artificial Intelligence" work-study program. The person recruited will be fully integrated into a pedagogical team of about twenty people and will be involved in particular in the implementation of this new learning path.


  • It will provide basic teaching in a wide spectrum of scientific and technological informatics (software development, databases, web, various subjects around data) to students and apprentices, participate in the management of apprenticeship training (follow-up of apprentices, organizational and material context of schooling) and will be involved in relations with companies, natural partners in training through apprenticeship. This sensitivity to the links between training and enterprise (and more broadly training-enterprise-research) will be particularly appreciated.


  • CdD status (1 year renewable), MCF grid remuneration with possible resumption of seniority, teaching service 384h equivalent TD.


  • Application deadline: June 17, 2022 4:00 p.m.


  • Contact for more information: [email protected]


  • Official place of publication of the offer and application process: https://www.univ-nantes.fr/travailler-a-luniversite/offres-demploi-et-concours/lecole-polytechnique-de-luniversite-de-nantes-recrute-un-enseignant-chercheur-contractu el-type-lru-informatique


PhD student recruitment Explainable deep learning models for time series analytics



  • We are looking for a Ph.D. student to join (the 1st of October 2022) the team MIDI (https://www.etis-lab.fr/midi/) of the Etis laboratory (CYU).


  • The candidate will pursue a Ph.D. degree in Computer Science in Deep Learning and Data Science areas, studying application to temporal data (time series).


  • The research activity will get coordinated by Professor Vassilis Christophides (https://www.etis-lab.fr/2022/01/13/vassilis-christophides/) and Associate Professor Michele Linardi (https://www.etis-lab.fr/2022/01/12/michele-linardi/). The Ph.D. project will also benefit from our current industrial collaborations.


  • The interested applicants can find attached to this mail all the details of the proposition and the information on how to apply.


  • Applicants should contact via email V. Christophides (Vassilis.Christophides@ensea. fr) and M. Linardi ([email protected]) with:


  • • A full curriculum vitae, including a summary of previous research experience.


  • • A transcript of higher education records.


  • • A one-page research statement discussing how the candidate’s background fits the proposed topic.


  • • Two support letters of persons that have worked with them.


PhD student recruitment Analysis and automatic evaluation of the surgical-dental procedure in a virtual training environment



  • title: Analysis and automatic evaluation of the dental surgery procedure in a virtual training environment


  • Summary: The thesis topic focuses on the design and implementation of models and tools for the automatic evaluation of the dental surgery procedure according to the observation and analysis needs of practitioners.


  • These gestures are analyzed from the captured movements of teachers and learners, and rendered in 3D within the virtual simulator "Virteasy" developed by the company HRV.


  • The thesis topic is part of the ANR EVAGO project on the instrumentation of virtual simulators for learning assistance and training in Dentistry.


  • The candidate must address the following elements to [email protected] and sebastien.george@univ-lemans. fr:


  • - CV and cover letter,


  • - report of the Master 2 internship (or 5A, if available, the pre-reports are accepted)


  • - report cards of the Master 1 and Master 2 (or 4A and 5A)


Research Scientist in Machine Learning and XAI (1 to 2 years fixed-term contrat) TotalEnergies/SINCLAIR



  • TotalEnergies is looking for a researcher in machine learning to join our team in Saclay (FRANCE).


  • We are looking for someone interested in explainability to join the SINCLAIR laboratory (industrial lab involving EDF, Thales and TotalEnergies).


  • If you are interested in developing and applying explainability approaches on industrial use cases, learn more about the offer and apply here:


  • https://krb-sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?partnerid=30080&siteid=6558&PageType=JobDetails&jobid=1954394#jobDetails=1954394_6558


Post-Doc offer (24 months) ERPI laboratory, Machine Learning / Education, University of Lorraine



  • Digital environments for learning are increasingly numerous in high schools and universities. The PLEIADES project (Lorraine Digital Environment Project for DurablES Learning) aims to deploy new digital environments and analyze their impacts. The use of data from these environments during educational sessions will improve our understanding of these new uses of digital technology for education, analyze and improve learning processes. On the scientific level, we will be interested in learning the data from the pedagogical sessions. We want to model the measurement and prediction of gain during pedagogical sessions with high school students and students from the University of Lorraine using machine learning models using data from digital environments. It will be a question of measuring and evaluating the impact of these digital environments for learning and of formulating recommendations to adapt their uses according to pedagogical typologies.


  • The candidate will join the research team of the PLEIADES project. PLEIADES (Lorraine Digital Environment Project for DurablES Learning of the University of Lorraine) aims to create an inclusive digital environment at the service of the university community. By mobilizing constant and quality support, the University of Lorraine wants to place digital technology through this project, at the service of weaving links between the university community and at the service of an embodied belonging and experience. Digital technology must be a catalyst for interactions and cooperation between all actors, to break distances (social, disciplinary, geographical) and to support the fundamentally collective dimension of learning, both that of knowledge and, beyond that, that of autonomy and discernment. This project is based on five programs:


  • PLEIADES-Territoires: create links between the university and the high schools of the Vosges territory by relying on an immersive environment in collaboration with the services of the rectorate;


  • PLEIADES-Trajectories: ensure the monitoring, progression and evaluation of skills through the use of an e-portfolio;


  • PLEIADES-Environment: enrich learning through the use of virtual reality technologies and advanced features on the course platform;


  • PLEIADES-Relations: boost language learning by connecting university students with students from foreign universities.


  • PLEAIDES-Espaces: create virtualization spaces to meet the needs of students.


  • The candidate will work on the "PLEIADES-Territories" axis. It will ensure the collection of data, the learning of data and the analysis of data and uses and the restitution of results. The candidate will work in collaboration with two other post-doctoral fellows working on 2 other axes of the PLEIADES project.


  • Desired skills: - Thesis in Computer Science.


  • - Data collection or training or recommendation systems or data mining.


  • - Knowledge of Living Lab approaches or collaborative workshop facilitation would be a plus.


  • Contract Start Date: September 2022.


  • Salary: from 2130€ gross to 2948€ gross (to be negotiated according to the experience of the researcher)


  • Duration of contract: 24 months.


  • To apply: Send CV and cover letter to davy.monticolo@univ-Lorraine. fr


  • Deadline: June 5, 2022


3-year Fully-funded Phd Fellowship at GREYC (France) and MTU (Ireland) on Multimodal Access to Information in the situation of Textual Blindness



  • The research laboratory GREYC UMR 6072 (https://www.greyc.fr/) and the Munster Technological University (Ireland) are launching a call for applications for a PhD student position in the field of information access in text-blind situation.


  • In the face of the increasingly widespread advent of nomadic and ubiquitous access to information, and with a view to reducing the digital divide, it is imperative to allow the greatest number of people to understand the informational and organizational structure of web pages, which is at the same time global, naturally interactive and independent of the support.


  • The Web is characterized by a multi-support, multi-application, multi-task, multi-object logic that builds a visual and organizational structuring of the information often complex. When they are well calibrated, the typographic and layout properties allow a user to quickly pick up a large number of clues, and to activate non-linear interactive strategies consistent with reading objectives. But certain user populations may have difficulties due to pathologies related to both the perceptual and cognitive spheres; a degradation of decoding capacities (semantic, logical or visual) of these highly structured contents is then observed.


  • We group together under the term of "textual blindness" this inability to easily interpret documents for perceptive reasons (visual impairment, blindness) or cognitive reasons (receptive dysphasia, mental handicap).


  • This thesis, at the intersection of Natural Language Processing and Human-Computer Interaction, aims at exploiting the results obtained in two projects TactiNET (https://www.youtube.com/watch?v=jAqYQzfL-is) and TagThunder (https://www.youtube.com/watch?v=vrET36OcjJs), to develop a multimodal interaction model in the context of information access in a text-blind situation.


  • Thus, the results of this work have allowed us to make the hypothesis that a multimodal platform integrating the two modalities would substantially improve the perception/action loop for the interpretation of web documents in a situation of textual blindness.


  • This thesis will aim at designing an architecture that (1) integrates haptic and sound modalities, and (2) promotes reading paths based on multi-grain semantics.


  • The device will propose a multimodal navigation oriented by (1) textual units belonging to a visual, logic and thematic organization within the documents and (2) the hierarchical links they have with each other or with the semantic concepts they convey.


  • The successful candidate should have a Master's degree or equivalent in computer science or electronics.


  • A solid background in computer science is required and knowledge in electronics and natural language processing would be appreciated.


  • If you are interested in this position, please send the following information to Gaël Dias ([email protected]), Fabrice Maurel ([email protected]) and Mohammed Hasanuzzman ([email protected]):


  • - Detailed CV - Transcripts of undergraduate and graduate degrees. - Letters of recommendation (up to 3 maximum)


  • Applications will be considered until the position is filled or before July 31, 2022.


  • For more information, please contact Gaël Dias directly ([email protected]) or Fabrice Maurel ([email protected]) or Mohammed Hasanuzzman ([email protected]).