Post-doctoral research position Analysis of time series in robotic surgery



  • 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)


  • Host team: LINKMEDIA


  • 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.


  • (2) Laboratoire des Sciences du Numérique de Nantes : UMR CNRS 6004


  • 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)


  • Simon Malinowksi http://people.irisa.fr/Simon.Malinowski/ Christine Sinoquet https://christinesinoquet.wixsite.com/christinesinoquet


  • Pierre-François Marteau https://people.irisa.fr/Pierre-Francois.Marteau/ Pierre Jannin https://medicis.univ-rennes1.fr/members/pierre.jannin/index


Post-doctoral position in Collaborative Learning in Saclay (Paris)



  • The ANR Project HERELLES offers a two years Post-doctoral position Interactive multi-paradigm collaborative learning for time series analysis


  • The post-doctoral project aims to propose an innovative method of interactive multi-paradigm collaborative learning, which combines supervised and non-supervised methods while allowing interaction with the expert.


  • The candidate will propose and define novel mechanisms that allow supervised and unsupervised methods to collaborate efficiently to reach a classification consensus. The modalities of information exchange between them will have to be specified. He/she will also have to define a protocol for interaction between the user and the learning methods through the use of constraints. Finally, he/she will have to concretely implement the proposed approaches to allow their testing and validation.


  • Location: Saclay (AgroParisTech campus, 22 place de l'Agronomie, 91120 Palaiseau)


  • Duration: One year (renewable once) – starting as soon as possible


  • Salary: between 2500€ and 2700€ before taxes (brut) monthly according to past experience


  • Contact: Antoine Cornuéjols [email protected] and Pierre Gançarski, [email protected]


  • EXPECTED PROFILE - PhD in Computer Science and specialized in Machine Learning/Data Mining.


  • - Strong knowledge in Data Science and more particularly in standard classification and clustering methods. Experience in using collaborative/ensemble models or constraint integration would be a plus.


  • - Good verbal (English or French) and written (English) communication skills.


  • - Interpersonal skills and the ability to work individually or as part of a project team.


  • TO APPLY Send an email to [email protected] included curriculum vitae, list of publications, letter of motivation and contact details of three references. Applications will be accepted until the position is filled.


Thesis offer: Anonymization of multimodal speech, Inria (Nancy)



  • Inria proposes a funded thesis on speech anonymization multimodal. For more details and to apply, see: https://jobs.inria.fr/public/classic/en/offers/2022-05013


  • Applications will be reviewed on the fly until June 30.


  • Cordially, Emanuel Vincent


Research Engineer in Information Extraction



  • This offer is part of a collaboration between INRIA (Almanach team) and the Ministry of Ecological Transition (MTE) on extracting information from impact study files (for example, a project to extend a wastewater treatment plant or deployment of a wind farm).


  • Detailed description of the offer (and application): https://jobs.inria.fr/public/classic/en/offers/2022-04928


  • Main activities : - Study the methods of acquiring knowledge, information extraction and classification (annotation of segments) that could be used as part of the project


  • - Study the different approaches


  • - Explore the research steps proposed through the development of proof of concepts and conducted experiments on available data


  • - Interactions with MTE experts to determine the relevant information to be extracted from the files and for conduct evaluations of the tools developed


  • - Possible supervision of a manual annotation campaign and/or validation of pre-annotations


  • - Write a research report to document the project.


  • Required skills: - Python (advanced), Perl (notions) - Experience machine learning libraries and deep (Pytorch, TensorFlow, Keras, transformers huggingface, Scikit-Learn)


  • - Experience in neural network architectures (including transformers) and language models


  • - Academic experience in processing algorithms automatic natural language, in particular on the extraction information and/or the acquisition of knowledge


  • - Experience in a research team


  • Team presentation: ALMANAC Automatic Language Modeling and Analysis & Computational Humanities http://almanach.inria.fr/ https://www.inria.fr/fr/almanac


  • Candidacy: - on the site https://jobs.inria.fr/public/classic/en/offers/2022-04928


Job : CDD (12 months), Software Engineer M/F, University of Lorraine



  • as part of the Palamède project, led by S. Ferey, MSH Lorraine, we are looking for an engineer who can work on improving the TACT corpus transcription and annotation platform.


  • https://www.univ-lorraine.fr/travailler-a-l-ul/wp-content/uploads/sites/13/2022/05/OFFRE-RECRUTEMENT-EXTERNE-1.pdf


  • Our CORLI consortium is participating in this project as part of its Collaborative Corpus Annotation axis .


  • Profile of computer linguist loving to develop welcome!


Machine Learning Heuristic for Constraint Programming PhD thesis - CIFRE.



  • Candidate We are looking for a highly motivated Engineering School or Master’s degree candidate in Computer Science who is motivated by the following fields:


  • constraint reasoning, machine learning, deep learn- ing, reinforcement learning, artificial intelligence, theory of computing, algorithms, high-performance implementation, parallel programming.


  • We expect the candidate to love engineering, C++ coding, mathematics and to have good writing skills.


  • Please contact us at the email address below. Include a detailed CV and motivation letter, under- graduate and graduate marks, list of the courses followed, project or internship reports, name of two persons who can recommend you and/or recommendation letters, link to personal GitHub if any.


  • Working environment Supervision in the Paris Research Center will be done by Arnaud Lallouet, principal scientist and head of the Constraint Programming team. Gross salary is of 2600¿ the first two years and 2800¿ the last year.


  • The Paris Research Center of Huawei Technologies provides a high level scientific environment hosting many researchers on different topics ranging from communication theory to machine learning and cutting-edge hardware facilities.


  • It enjoys also a nice working environment on the Seine riverside with excellent restaurant and leisure zone with snooker. Contacts Arnaud Lallouet, Huawei Technologies Ltd, [email protected]


Funded thesis offer in AI



  • We are looking for a PhD student for a thesis in AI co-funded by UTT and URCA on the following topic:


  • "Prediction of links for the detection and design of energy systems in renewable and citizen energy communities".


  • Do not hesitate to contact [email protected] and/or francis.rousseaux@univ-reims. fr for any questions.


Funded thesis offer - Multimodal speech anonymization, Inria Nancy & Lille, France



  • Inria offers a funded thesis on the anonymization of multimodal speech . For more details and to apply, see


  • https://jobs.inria.fr/public/classic/en/offers/2022-05013


  • Applications will be reviewed over time until June 30.


PhD position : Multi-agent adaptive team pairing in an Open Science context



  • The candidate will work at the Computer Sciences department of LAMIH (UMR CNRS 8201), UPHF, Valenciennes, France. The working language could be French, good English ability is required.


  • Date: The expected startup date is September 1st, 2022, but may however be flexible.


  • Required competences for the applicant:


  • - Artificial Intelligence, Multi-agents systems - Java, Python programming. - Good understanding of blockchain protocols is appreciated.


  • How to apply & contacts:


  • Applicants must submit an official academic transcript of records for their bachelor and masters education. It is a requirement to hold a masters or an equivalent degree for being considered for this position. At least two references (name, position, e-mail, and telephone number) should be included in the application.


  • Candidates should send by e-mail a CV and a statement of purpose to: - Mourad Abed, [email protected] - René Mandiau, [email protected] - Emmanuel Adam, [email protected]


21 PhD grants at the Faculty of Computer Science of the Free University of Bozen-Bolzano in Italy



  • 21 three-year grants are offered by the Faculty of Computer Science of the Free University of Bozen-Bolzano in Italy for its PhD programme. Each grant amounts to 51,000 € (i.e., 17,000 euro per year, net after taxes); for research visits abroad the grant increases up to 50%. Additional substantial extra funding (including a personal budget of 2,500 euro per year) is available for participation in international conferences, schools, workshops, research visits. Some of the PhD grants are supported by FBK, University of Umeå, and by software companies, and interested candidates might carry out their PhD research in collaboration with these external partners. The language of the PhD programme is English.


  • The deadline for applications will be on the 1st of July, 2022.


  • For more info, the call, and applications look at: www.unibz.it/en/faculties/computer-science/phd-computer-science


  • The university is located in one of the most fascinating European regions, the Dolomites. This young university has already established itself as an important research institution, both in Italy and abroad. According to the Times Higher Education World University Rankings, the university is the ninth world’s best small university and it is the second best young Italian University, and its Faculty of Computer Science is ranked among the 150 best Computer Science departments worldwide (in absolute terms) and it is the 21st best Computer Science department worldwide for scientific citations. According to the same ranking, the Faculty of Computer Science of the Free University of Bozen-Bolzano is the third best Italian computer science department, it is the best for international outlook Italian computer science department, and it is the best for citations Italian computer science department.


  • The KRDB Research Centre for Knowledge and Data of the faculty is widely recognised as one of the internationally leading groups in Artificial Intelligence Knowledge Representation research, with a synergy between foundational and application-oriented research. Among the various available PhD topics (fully described in the call), the KRDB Research Centre is looking for PhD students interested in:


  • Logic-based languages for knowledge representation; Intelligent data access and integration;


  • Semantic technologies; Conceptual and cognitive modelling; Data-aware process modelling, verification, and synthesis;


  • Business process monitoring, mining, and conformance; Temporal aspects of data and knowledge; Extending database technologies;


  • Visual and verbal paradigms for information exploration; Reasoning with uncertain and imprecise knowledge.


  • To get in contact with the KRDB Research Centre and discuss the opportunities of this call contact prof. Alessandro Artale at [email protected]


PhD position on Data Profiling, Protection and Sharing



  • PhD position on Data Profiling, Protection and Sharing* PSL, Université Paris Dauphine


  • We have an opening for a PhD position with the objective to develop new solutions to help data providers who wish to share their data to better understand it, and to choose the best-suited data protection policies.


  • The PhD Student will be investigating techniques for profiling and linking datasets that would help data providers to gain insight into their data, to estimate its (economic) value, and to choose data protection strategies that go beyond privacy protection to take into account the protection of the data provider's economic assets.


  • The PhD thesis is part of an interdisciplinary project involving another PhD thesis on data governance in the field of management sciences. We anticipate that the interaction between the two doctoral students will lead to interdisciplinary contributions in addition to computer science-focused solutions.


  • The PhD candidate will work in close collaboration with members of the data science team of the Paris Dauphine University. The problems investigated and solutions developed will be guided and validated within case studies in the fields of health and economics.


  • The successful candidate will enroll as a PhD student in the Computer Science department of the Paris-Dauphine University (under the co-direction of myself and Prof. Daniela Grigori) and will become a member of the Data Science team of the same university. Paris Dauphine University is located in the city of Paris, and is a member of PSL (Paris Sciences et Lettres).


  • We seek strongly motivated candidates prepared to dedicate to high quality research.


  • The candidate should have (or be close to obtaining) a Master's degree or equivalent in computer science or applied mathematics. Starting date September/2022.


  • Interested candidates are invited to send the following to [email protected] and [email protected]


  • - academic CV - academic transcripts of BSc and MSc


  • - one page motivation letter explaining why the candidate is suitable for the position


  • - contact details of two referees


2 Postdoc positions in planning and deep RL for MASs -- Citi-lab / Inria Lyon



  • We are recruiting 2 postdoc researchers for one year on planning and (deep) reinforcement learning for 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 information on how to apply.


  • Applicants should contact via email [email protected] and olivier. [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. • Salary: About 2320e per month. • Location: The post-doc will take place in INSA Lyon, CITI-lab, within the Inria Chroma team.


  • – Lyon, France – INSA Lyon (https://www.insa-lyon.fr), – CITI INRIA Laboratory (https://www.inria.fr, http://www.citi-lab.fr) • When: The post-doc shall start as soon as possible in 2022.