Cross-lingual and cross-domain terminology alignment*

Interested in joining a young NLP group of 10+ people located in a historical town by the Atlantic Ocean? And walk 10 minutes from the lab to the beach. We have open positions in the *context of recent Horizon 2020* projects: Embeddia and NewsEye as well as related local projects. In the last 2 years, we have among others published long papers in *CORE A* and A* conferences such as ACL, JCDL, CoNLL, ICDAR, COLING, ICADL, etc.

*Location*: L3i laboratory, La Rochelle, France

*Duration*: 2 years (1+1), with possible further extension *Net salary range*: 2100€-2300 € monthly

*Context*: H2020 Embeddia project and regional project Termitrad *Start*: September 2022 (tentatively)

Keywords: *terminology alignment, cross-lingual word embeddings, named-entity recognition and linking, deep/machine learning, statistical NLP, (text) mining*.

Applications are invited for a postdoctoral researcher position around the topic of project Termitrad: keyword and terminology alignment 1) across languages and 2) across domains. In short, the overall objective of the project is to improve the relevance of the keywords describing research papers (and, time allowing, the quality of abstracts). One the one hand (cross-lingual alignment), we will rely on a corpora of journal articles with both French and English keywords and abstracts, both in as written by authors and in versions curated by experts. On the other hand (crossdomain alignment), we will work with use cases provided by researchers from different fields using different terms to describe similar concepts.

To address this very project, the project team will consist of senior staff, 2 post-doctoral researchers and 2-3 PhD students, one of which is jointly supervised in the Józef Stefan Institute in Ljubljana, coordinator of H2020 Embeddia. In this context, you will first be in charge of building a state of the art of existing related approaches, tools and resources, then to conduct further research and experiments, as well as participate in the supervision of PhD students.

Who we search for: - PhD in statistical NLP, IR, or ML, ideally with further postdoctoral experience

- proven record of high-level publications in one or more of those fields

- fluency in written and spoken English (French language skills are welcome but unnecessary)

Applications including a CV and a one-page research statement discussing how the candidate's background fits requirements and topic are to be sent to by email to [email protected], strictly with the subject "Embeddia/Termitrad postdoc application".

*Application deadline: 14 June 2022.*

Starting date: November 01, 2022

Application deadline: June 20th, 2022

Interviews (by preference): June 28th, 2022

Keywords: natural language processing, citation classification, transfer learning, deep learning

Context The NanoBubbles ERC project objective is to understand how, when and why science fails to correct itself. The project’s focus is nanobiology and it combines approaches from the natural, computer science, and social sciences and the humanities (Science and Technology Studies) to understand how error correction in science works and what obstacles it faces. For this purpose, we aim to trace claims and corrections in various channels of scientific communication (journals, social media, advertisements, conference programs, etc.) via natural language processing.

The challenge is to analyse the rapidly evolving ecology of online comments complementary to scientific records.

Project objectives Although there is a consensus that scientific knowledge is constructed through critical debate, critical citations are rare in the scientific literature and difficult to identify. Nevertheless, it can be hypothesized that they would constitute a means of detecting controversy about a particular topic, including the retrieval of claims and counter-claims. The PhD student will have to explore this line of research by taking advantage of classification and citation polarity detection methods. But since controversy often takes place outside of the scholarly communication arena, he/she will also have to explore alternative important sources such as PubPeer, Twitter and specialized blogs.

Recent works in NLP [Bakhti2018,Jurgens2016,Pride2019,Yu2020] explore citation behaviours and habits. New large language models [Zhang2022] may be useful to explore approaches suited to understand error correction in the field of nanobiology, Information extraction is useful in other domains such as medicine [Kocabiyikoglu2021], errors detection [Park2022,Labbe2020] or Natural Language Understanding [Desot2022], for instance.

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

Programming experience in Python and in a deep learning framework. Previous experience in NER, RE and dataset manipulation would be a plus.

Scientific environment The thesis will be conducted within the Sigma and Getalp teams of the LIG laboratory (http://sigma.imag.fr/ and https://lig-getalp.imag.fr/). The GETALP team has strong expertise and track record in Natural Language Processing, SIGMA team strong expertise in Database and NLP. The recruited person will be welcomed within the teams which offer a stimulating, multinational and pleasant working environment.

The means to carry out the PhD will be provided both in terms of missions in France and abroad and in terms of equipment (personal computer, access to the LIG GPU servers).

The PhD student will collaborate with several team members involved in the ERC Nanobubbles project, in particular with researchers from the LISIS lab (Marne-la-vallée, France), University of Sorbonne Paris-Nord as well as researchers from Maastricht University, Radboud Universiteit and University of Twente based in the Netherlands.

Instructions for applying Applications are expected until July 5th, 2021. They must contain: CV + letter/message of motivation + master notes + be ready to provide letter(s) of recommendation; and be addressed to Cyril Labbé ([email protected]), François Portet ([email protected]) and Frédérique Bordignon ([email protected]). We celebrate diversity and are committed to creating an inclusive environment for all employees

Applications will be considered case-by-case. It is therefore advisable to apply as soon as possible.

Commitment & contract: up to 18 months - collaboration contract Location: Istituto Italiano di Tecnologia, Via Enrico Melen 83,Genova - Italy

WHO WE ARE At IIT we work enthusiastically to develop human-centered Science and Technology to tackle some of the most pressing societal challenges of our times and transfer these technologies to the production system and society.

Our Genoa headquarter is strictly inter-connected with our 11 centres around Italy and two outer-stations based in the US for a truly interdisciplinary experience.

YOUR TEAM You’d be working in a multicultural and multi-disciplinary group, where Physicists, Engineers, Computer Vision and Computational Intelligence experts collaborate, each with their own expertise, to carry out common research. The Pattern Analysis and Computer Vision (PAVIS) Research Line is coordinated by Dr. Alessio Del Bue leading a team of more than 20 units working on advancing the state of the art in Computer Vision and Machine Learning.

The research focuses on novel computational models related to graph neural networks and constrained deep learning to solve challenging problems in life science and physics.

Within the team, your main responsibilities will be: Investigate and develop new Deep Learning methods for large-scale graph data structures Supervise PhD students

WHAT WOULD MAKE YOU SHINE A PhD in Computer Science, Machine Learning, Computer Vision and similar disciplines Documented experience on the Deep Learning, with a special focus on Graph Neural Networks

Strong programming ability (Python preferred) A relevant publication record The ability to properly report, organize and publish research data Documented experience in coaching junior scientists Good command in spoken and written English

EXTRA AWESOME Experience on Deep Learning tools such as Pytorch, Tensorflow, etc... Knowledge of Graph Theory Good communication skills Strong problem solving attitude High motivation to learn

Spirit of innovation and creativity Good in time and priority management Ability to work in a challenging and international environment Ability to work independently and collaboratively in a highly interdisciplinary environment

COMPENSATION & BENEFITS Competitive salary package for international standards Private health care coverage Wide range of staff discounts Candidates from abroad or Italian citizens who permanently work abroad and meet specific requirements, may be entitled to a deduction from taxable income of up to 90% from 6 to 13 years.

WHAT’S IN FOR YOU? An equal, inclusive and multicultural environment ready to welcome you with open arms. Discrimination is a big NO for us! We like contamination and encourage you to mingle and discover what other people are up to in our labs!

If paperwork is not your piece of cake, we got you! There’s a specialized team working to help you with that, especially during your relocation! If you are a startupper or a business-minded person, you will find some exceptionally gifted professionals ready to nurture and guide your attitude and aspirations.

If you want your work to have a real impact, in IIT you will find an innovative and stimulating culture that drives our mission to contribute to the improvement and well-being of society!

We stick to our values! Integrity, courage, societal responsibility and inclusivity are the values we believe in! They define us and our actions in our everyday life. They guide us to accomplish IIT mission! If you feel this tickles your appetite for change, do not hesitate and apply!

HOW TO APPLY Please submit your application using the online form https://iit.taleo.net/careersection/ex/jobdetail.ftl?lang=it&job=2200003E and including a detailed CV, university transcripts, cover letter (outlining motivation, experience and qualifications)and contact details of 2 references.

Application’s deadline: June 26, 2022

We inform you that the information you provide will be used solely for the purposes of evaluating and selecting professional profiles in order to meet the requirements of Istituto Italiano di Tecnologia.

Your data will be processed by Istituto Italiano di Tecnologia, based in Genoa, Via Morego 30, acting as Data Controller, in compliance with the rules on protection of personal data, including those related to data security.

Please also note that, pursuant to articles 15 et. seq. of European Regulation no. 679/2016 (General Data Protection Regulation), you may exercise your rights at any time by contacting the Data Protection Officer (phone Tel: +39 010 28961 - email: [email protected] - kindly note that this e-mail address is exclusively reserved for handling data protection issues.

Please, do not use this e-mail address to send any document and/or request of information about this opening.

CONTEXT AND MAIN PURPOSE ***

The Connected Environment & Distributed Energy Data Management Solutions (OpenCEMS) industrial chair addresses the issues that businesses and communities encounter when handling data management in their connected environments.

The OpenCEMS research group aims at designing, implementing and deploying software solutions within Small and Large Scale Distributed/Connected Environments for better data collection/aggregation, information retrieval, and knowledge extraction.

More details can be found here: https://opencems.sigappfr.org/

*** DESCRIPTION OF THE RESEARCH & OBJECTIVES ***

Connected environments are typically defined as physical real world infrastructures hosting sensor networks that record phenomena from the real world. However, the increasing number of sensors in environments leads to a huge increase in data collection, making data retrieval from resources a big challenge. Resource indexing is the process of assigning each device an index. In other words, each device will have knowledge about its location and the zones of other sensors. This implies that sensors, that cannot store the entire environment's information, will forward the query to another device or to the requested zone.

In addition, uncovered zone discovery is essential to reduce time and resource consumption considerably. The global objective of this doctoral fellowship is the design and implementation of the following modules in the OpenCEMS platform: (i) Generate (centralized and distributed) resources index for a connected environment, (ii) Execute different types of queries (proj ection, selection, etc.) (iii) Implement different discovery protocols while considering resource/network capacities, and (iv) Deploy an experimental protocol to evaluate the proposed approaches.

*** REQUIREMENTS *** · The ideal candidate has a master degree in computer sciences · A previous experience in Indexing would be a plus · Outstanding analytical competence, · Strong interest in research (Data Management, Machine learning, Information retrieval)

· Excellent scripting and coding skills (in Python) · Excellent Communication skills · Autonomous and team working capabilities.

*** OFFER DETAILS *** · The Phd student will have the opportunity to work in a research group that gathers academic, and industrial partners. This environment allows the student to participate in research gatherings, conferences, and visiting/working in different environments (e.g., in a research lab, partner institutions, and companies).

· Duration: 36 months. · Gross Salary: 1870 euros / month (which includes extra gratification for teaching duties - 32h per year) · Main host institution: LIUPPA/OpenCEMS research group.

*** APPLICATION INSTRUCTIONS ***

Please send your applications (in PDF format) to the following contact: [email protected] The application (written in English) should include: · A Curriculum Vitae (including your contact address, work experience, publications, software repositories) · A cover letter

· Your Master degree grade transcripts and ranking · Two recommendation letters · Two of your best publications/implementations

Deadline for applications: June 25th, 2022. Start date: September 1st, 2022 (negotiable).

Screening of applications starts immediately and will continue until a candidate is selected. Therefore, early applications are encouraged.

*** EVALUATION CRITERIA *** Candidates will first be selected based on their application file. Those selected after this first step, will then be interviewed. Application files will be evaluated based on the following criteria:

- Grades and ranking during your Master degree, steadiness in your academic background

- English language proficiency - Candidate's ability to present her/his work and results

Work experience similar to an internship in a laboratory - or likewise; previously achieved research work (reports, publications).

Qualifications 1. PhD in machine learning from an accredited university 2. Excellent communication skills, both verbal and written in English 3. Skills in Python language

4. Communication skills in French 5. Experience in uncertainty estimation 6. Experience in physics application is a plus

Salary & benefits The salary will depend on the applicant’s profile and experience. The position comes with various social benefits (e.g. health insurance). This position is open for one year.

Application and contacts To apply send an updated CV and a motivation letter to: Amandine DUTERME ([email protected]) Fabrice GAUDIER ([email protected]) Laurence CORNEZ ([email protected])

The position is open immediately. Review of applications will begin as soon as applications are received and continue until the position is filled or the deadline of January 1st 2023 is reached.

Qualifications 1. PhD in machine learning from an accredited university

2. Excellent communication skills, both verbal and written in English 3. Programmation in Python language (Tensorflow will be used) 4. Communication skills in French

5. Experience in convolutional network using times series is a plus 6. Experience in physics application is a plus

Salary & benefits The salary will depend on the applicant’s profile and experience. The position comes with various social benefits (e.g. health insurance). This position is open for one year, renewable once.

Application and contacts To apply send an updated CV and a motivation letter to: Laurence CORNEZ ([email protected]) Amandine DUTERME ([email protected])

The position is open immediately. Review of applications will begin as soon as applications are received and continue until the position is filled.

We are recruiting 2 postdoc researchers for one year on planning and (deep) reinforcement learning for single- or multi-agent systems, e.g., decentralized partially observable Markov decision processes, or partially observable stochastic games.

The two researchers will join the Inria Chroma team at CITI laboratory / Inria Lyon.

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

Applicants should contact via email Jilles S. Dibangoye (jilles-steeve. [email protected]) with:

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

Please find a post doc offer to be able at the beginning of October at ATILF, Nancy in collaboration with the CHRU, the CRAN and the IECL

https://docs.google.com/document/d/1smS0vKSL8vM1qnI1NrGWSqNaDOFmMeVM/edit?usp=sharing&ouid=110408077992921256728&rtpof=true&sd=true

https://docs.google.com/document/d/ 1smS0vKSL8vM1qnI1NrGWSqNaDOFmMeVM/edit?usp=sharing&ouid=110408077992921256728&rtpof=true&sd=true

Context Collaboration between a LIMOS / CNRS laboratory of the University of Clermont Auvergne and a young innovative company Jeolis Solutions, both located in Clermont-Ferrand, in the field of e-Health and more specifically Therapeutic Patient Education (ETP[1]). Environmental constraints and the health crisis such as that of Covid-19 argue for an absolute need to quickly develop intelligent digitalization in order to achieve a motivating, fun and personalized e-FTE.

Missions In the perspective of the article [1], it was stated the possibility of improving the logical expressiveness of the program by using other approaches such as ASP (Answer Set Programming) in order to limit the use of imperative code.

The missions of the person recruited will be the implementation of tools to:

Combining the best of all worlds OWL2 and ASP OWL2 for the static aspect of knowledge (TBox and ABox + consistency check by classification of individuals), as proposed in the Protected editor. In addition, OWL2 allows inheritance between classes and relationships.

ASP for the dynamic aspect of knowledge and the relevance of logical rules with negation(s), constraints and non-monotonous

The theoretical aspect of this hybridization was proposed in Hexlite [2] but we believe that an implementation in all Python would facilitate adoption.

Establish a DMN transcription to ASP Writing an ASP program is not yet within the reach of business experts in the industrial world, which does not facilitate the adoption of ASP despite powerful solvers. However, there is the DMN (Decision Model and Notation) standard of the OMG consortium which allows manufacturers to write decision systems from simple Excel tables. It would be interesting to have a tool allowing the transition from DMN to ASP, as was recently proposed in cDMN [3].

The interest would be to allow psychologists, pedagogues to write, improve, test progression strategies more easily, faster than currently, without going through an expert engineer specialized in Knowledge Engineering.

Work context The person recruited will join the LIMOS Data, Services and Intelligence theme but will be made available to Jeolis Solutions' R&D team for 80% of their time (application of the recovery France plan – preservation of R&D employment in companies).

The fixed-term contract is for a period of 19 months, and must begin before the end of September 2022, adaptable according to the availability of the selected person.

Expected skills · Holds a Master's degree in Computer Science (obtained in 2019, 2020, 2021 or 2022) with a strong background in Python development

· Knowledge/experience of semantic web standards (OWL2, SWRL...) and also in logic programming (PROLOG, Answer Set Programming...)

· Knowledge in Knowledge Engineering

· Git Code Manager tool experience and Agile methodology

· Respect for deadlines, rigor, organization, ability to work in multidisciplinary teams

Dear all, We are _urgently_ seeking candidates for a PhD on "Fresco reconstruction using machine learning".

The funding concerning that PhD is already acquired but the PhD must start in next September/October.

The detailed offer, instructions to apply, as well as application link can be found on this page:

https://nicolaslerme.fr/my_docs/sujets/these_2021-2022.pdf

We offer PhD funding in computer science (HMI, ergonomics) on the digital accessibility of textbooks in primary school for a period of 3 years.

This PhD will take place between the CNAM and the Learning Planet Institute in Paris under the supervision of Jérôme Dupire and Caroline Huron.

It is part of the ANR MALIN project, which aims to automate the adaptation of textbooks for children with disabilities.

Candidate and candidates must send to [email protected], [email protected], [email protected], [email protected] the following elements: CV, cover letter, Master 2 notes

We are looking for a Ph.D. student to join (September/October 2022) the Software Safety and Security Lab., Commissariat à l'Energie Atomique (CEA), Paris-Saclay, France.

Following recent promising results [1], the candidate will pursue a Ph.D. degree in Computer Science in AI for Software Verification, studying application of constraint acquisition to automated software specification inference.

The research activity will get coordinated by Sébastien Bardin (CEA Paris), Nadjib Lazaar (LIRMM, Montpellier) and Arnaud Gotlieb (Simula, Oslo).

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 Sébastien Bardin ([email protected]), Nadjib Lazaar ([email protected]), Arnaud Gotlieb ([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.

The story of 3DS OUTSCALE began in 2010 with one goal: to ensure the sovereignty of data and guarantee its security on a daily basis.

Subsidiary and strategic partner of Dassault Systèmes, 3DS OUTSCALE has established itself as the Hyper-Trusted Cloud by offering highly qualified Infrastructure Cloud services: ISO 27001, HDS, SecNumCloud...

To ensure the quality of our services and master their technological core, we have developed our own IaaS orchestrator: TINA OS, which is continuously evolving through the innovation of our R&D department.

You will join a human company, composed of Passionate Outscalians· driven by technology to learn continuously in a pleasant atmosphere.

We are proud to see our teams grow in a context of perpetual growth. We are looking for talents with strong values, passionate about the challenges of the Cloud!

Being a company in perpetual growth, and always looking for new talent, we are recruiting several Cloud Evangelist to strengthen our teams.

Your missions You will be in charge of:

Work closely with 3DS OUTSCALE's technical and sales teams to identify educational content. Define and design training programs/pathways related to 3DS OUTSCALE's cloud services and offerings for employees, customers and partners of the company. Identify relevant partners and tools in line with the company's training programs.

Validate the adequacy between training programs and the expectations of customers, internal managers and partners. Produce educational materials related to 3DS OUTSCALE's offerings and services in various forms (blog posts, white papers, videos, Powerpoint presentations, reports and educational materials, etc.) Attend/Participate in professional conferences.

Intervene with academic and industrial partners. Keep up to date with developments in the field of cloud and 3DS OUTSCALE services and offers. Work as a team with stakeholders (internal training, education program, sales, etc.) Apply a continuous improvement approach to training and adapt it according to learner feedback and internal needs. Create and develop new paths and partnerships.

Your profile Higher education in computer science type Bac + 4 /5 or Engineer, you have an experience of about 5 years in a consulting company and / or a computer training organization. You have excellent interpersonal skills and an ability to learn new technologies.

You have good knowledge of the technical ecosystem: Programming, Cloud Computing, System and Networks. A good level of English is essential. Cisco-type network certification is a plus.

Our advantages Teleworking: up to 2 days a week depending on the organization of the team Working from the province in a coworking space Co-optation premium Employee savings schemes Participation and profit-sharing bonuses based on the company's results Swile Card (9€/day)

Yuco (for sports sessions between colleagues) CSE (travel discounts, cinema tickets, parks, sports subscriptions...) Application of the sustainable mobility package

The Diversity of 3DS OUTSCALE also finds its expression in our recruitment policy which favors equal opportunities, the diversity of individuals within our teams. --

Duration of the contract (if open to contract workers): 1 year (renewable until the end of the project as of May 31, 2024)

Missions and activity Duties: The engineer is responsible for ensuring the administrative, logistical and financial implementation of the PRRI autOCampus, within the GIS neOCampus, and to monitor its execution and coordination or scientific foresight.

The position offered concerns more specifically the coordination of structuring, animation and prospective operations, centered around scientific policy in connection with intelligent and sustainable mobility.

Main activities : Scientific component • Perform documentary research related to the discipline of specialization of the candidate, in interaction with the themes of the PRRI; • Exercising a scientific and societal watch; • Take and manage the contacts of the requested experiments

• Participate in the collection of data and ensure their analysis and synthesis, in connection with experts and partners; • Participate in the creation, design and production of reports related to the project;

• Participate in the organization of planned scientific events; • Participate in the writing of articles for specialized scientific journals and for popular magazines;

• He/she will regularly report on the progress of his/her assignments to the Board scientist from the PRRI autOCampus platform and the GIS neOCampus • He/she will be required to meet the requested service providers and the project stakeholders, of which he will be one of the ambassadors;

Administrative component • Manage and coordinate the PRRI autOCampus project • Manage the coordination of the project with the various internal actors at the university, partner establishments and donors (GIS neOCampus, the Occitanie region)

• Ensure the planning, administrative and operational management and monitoring of the project • Coordinate, in conjunction with the UT3 Major Future Projects Unit and the Committee

Scientist of the autOCampus platform, project management, as well as the modeling and financial justification • Manage the activities and the internet and external communication of the platform • Produce reports for each of the actors involved in the project (project leaders, funders, steering bodies) • Produce indicators and reports relating to the project

Associated activities: • Provide advice and expertise and scientific production on the themes of smart and sustainable mobility. • Design internal procedures relating to legal administrative logistics and financial and support the formalization of deliverables

• Designing awareness-raising actions aimed at project leaders on the rules applicable to the management and execution of projects • Manage the activities and the internal and external communication of the platform, actions for the development of the project • Implement awareness-raising actions

for project leaders on the rules applicable to the management and execution of projects • Get involved in specialized professional networks

Required profile Knowledge: - Knowledge of project management - General knowledge of the rules and budgetary operation of a university - Know the rules of Budget Management and Public Accounting - General legal knowledge

- Level B2+ in English language One more - Mastery of one or more themes related to smart and sustainable mobility - Know the environment of higher education and public research

Technical and methodological know-how: - Master project management techniques - Implement analysis and synthesis skills - Scientific publication activity and editorial fluency - Know how to manage multiple actions and prioritize their activity independently and according to constrained schedules

- Master management techniques - Mastery of office software (Word, Excel, Power Point...) and technologies of information and communication (ICT) - Know how to report - Know how to lead meetings

Behavioral knowledge: - Know how to work in a team, in a network and in interaction by adapting to interlocutors varied - Rigor, organization and reliability - Sense of public service - Sense of listening and dialogue, interpersonal skills - Demonstrate autonomy - Being a source of proposals and a driving force in the development of projects

Level and diploma required / experience desired: Bac +8. Possess a doctorate in one of the following fundamental disciplines: sciences management, computer science, mathematics, geography, law. Previous experience within a research group (or similar) or an activity related to research and researchers will also be welcome experiences in the organization of congresses, meetings or conferences and as a project assistant.

Application methods Job Information For more information on the position, do not hesitate to contact Ms. Marie-Pierre Gleize: [email protected])

CV and motivation letter to be sent exclusively to the following address: [email protected]

The university implements an equal opportunity policy and encourages applications from qualified women and men, excluding any discrimination.

Key words: machine learning on time series, clustering, classification, average time series

Context Surgical robotics is now widely used with, for instance, more than 5000 Da Vinci systems and one million procedures performed worldwide. Surgery is a complex activity, in a very small anatomical volume, and with a lot of variability between patients and between surgeons. The global objective of the two-year SPARS (Sequential Pattern Analysis in Robotic Surgery: Understanding Surgery) project led by the MediCIS team (LTSI (1), Inserm, Rennes 1 University) is to develop data analysis approaches being able to provide a better understanding of the surgical practice, from complex surgical data. The approaches will be developed thanks to the complementary skills available in the project’s consortium, including time series analysis. In this consortium, the IRISA laboratory (Rennes and Vannes) is calling for applications for a post-doctoral research position (duration two years) on time series analysis.

(1) Laboratoire Traitement du Signal et de l'Image

Missions In the SPARS project context, a trajectory compiles information on the 3D location of the tip of a surgical instrument at the hands of the surgeon, at a constant frequency. The candidate will be mostly involved in one of the three workpackages of the SPARS project. A first task will focus on clustering and classification for such trajectories. Various practical objectives are pursued, including the generation of a model corresponding to a cluster or a class, the characterization of operating modes specific to a type of patient or a type of surgeon, the provision of advice to practitioners in the case of robotic surgeries that are not or not very well documented, the identification of the level of expertise of a practitioner, the prediction of the surgical procedure to be chosen according to the type of patient. These investigations will use dissimilarity measures based on temporal alignment, as DTW [SC71] or elastic kernels as proposed in [CVB07], [CB17] and [M19a]. This task will also address co-clustering for trajectories. The investigations will focus on how to combine time series with other types of data for a co-clustering purpose, using either deep learning [XCZ19] if enough data is available, symbolic representation [BBC15] or latent block [BLN20] models that all need to be adapted to the specificity of kinematics data.

Once a cluster or a class is obtained, another task will be to compute an average trajectory from a set of trajectories. The practical objectives will be the following: highlight deviations from the average trajectory that are potentially interpretable (as characteristics of the practitioner, or of the patient, for example) ; identify the best operating mode to young practitioners or trainees if it is possible to correlate the operating mode with clinical results. Intuitively, on the graphical representation of a time series, variability related to temporality (phase) concerns the abscissa axis, and variability related to shape concerns the ordinate axis. To compute a consensus trajectory, the second task of the package will examine how to extract the atemporal form and the variable component related to temporality, assuming that this atemporal form may be interpreted as an approximation of the consensus. The problem of shape and phase separation has been studied in [PZ16], [SSV10] and [M19a]. The second task will examine how to improve the preliminary work in [M19b], notably by proposing other kernels.

Requirements for this position Doctorate in computer science, applied mathematics and computer science, or mathematics, with a specialization in machine learning and the following requirements:

- theoretical skills and experience in probability / statistics, applied mathematics, machine learning,

- strong knowledge and solid experience in temporal data analysis,

- publications in major conferences or journals in the field,

- mastery of data manipulation, relying on machine learning libraries, - programming experience, good programming skills (notably in Python) and technical ability to manage a code development project,

- ability to work in a team, and report on the progress of work.

Some knowledge in deep learning will be a plus.

The personal qualities expected are mostly autonomy and interest in interdisciplinarity (health), as well as writing skills (both in French and English). Fluency in French will be a plus.

Work environment Location: Institut de Recherche en informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 - Campus Beaulieu, 263 Av. Général Leclerc, 35000 Rennes

Duration: 24 months – Applications will be accepted until the position is filled (for recruitment by 1 December 2022 at the latest)

The successful candidate will work with four academic researchers from IRISA / Rennes / LINKMEDIA team (Simon Malinowski, Associate Professor in Computer Science), IRISA / Vannes / EXPRESSION team (Pierre-François Marteau, Full Professor in Computer Science), LS2N (2) / Nantes / DUKe team (Christine Sinoquet, Associate Professor with French Accreditation to supervise Research (HdR)) and INSERM / Rennes / LTSI MediCIS team (Pierre Jannin, Directeur de recherche INSERM, HdR). The successful candidate will collaborate with the partners in the project, among which the other post-doctoral fellow involved in the project and the project partners experts in surgery and in surgical data analysis.

Income: 2160,26 euros before taxes monthly

How to apply? Documents to be provided : - detailed Curriculum Vitae including a complete list of publications,

- letter of motivation indicating the candidate’s research interests and achievements to date, - a selection of publications,

- the PhD thesis manuscript, - Master 2 marks (with rank and number of students in the year) - letters of recommendation for the current year, - contact details of two referees (at least) with whom the candidate has worked (first name, surname, status, institution (give details of acronyms if applicable), city, e-mail address, telephone number)

Questions or application files (zip archive only) should be sent to the four contact persons below:

[email protected] [email protected] [email protected] [email protected] (SPARS project leader)