List of CNRS tenure tracks for CNRS Informatics

This tenure track in computational and/or digital biology applied to health is devoted to the development of therapeutic methods through multi-scale characterisation of the mechanics of biological responses, modelling of radiation-tissue interactions and associated image processing. The aim is to better understand, predict and control the plasticity and cellular/tissue dynamics of tumours by integrating their environment when they are subject to standard treatments or innovative strategies. The methodological challenges are therefore to observe, characterise and simulate multi-scale biological or biophysical phenomena by developing ex vivo numerical or biological models. The models obtained will be used to help make therapeutic decisions based on preclinical clinical or biological data, to gain a better understanding of treatment response processes and to optimise therapeutic strategies.

Host laboratory : 

• Laboratoire CRAN (CNRS/Université de Lorraine)

Significant research has enhanced our understanding of the potential of ideal, large-scale, error-free quantum computers. However, current technological progress only allows for the consideration of limited-size, imperfectly functioning devices. These systems could still achieve significant breakthroughs once their potential is better understood.
The tenure track aims to support this effort by recruiting a researcher in theoretical physics and/or computer science working on such systems. This could involve assessing their potential as computational tools, developing strategies to improve their accuracy, adapting algorithm development to existing platforms, or creating methods to better understand their robustness and dynamics using mathematical, algorithmic, analytical, and/or numerical tools. Candidates will propose a research project that integrates with one or more of the host laboratories.

Host laboratories :

• Centre de physique théorique (CPHT - CNRS/École polytechnique)
• Laboratoire d’informatique de Grenoble (LIG - CNRS/Université Grenoble Alpes)
• Laboratoire d’informatique de l’École polytechnique (LIX - CNRS/Institut Polytechnique de Paris)
• Laboratoire de physique et modélisation des milieux condensés (LPMMC - CNRS/Université Grenoble Alpes)

The project will be part of the joint LaBRI and SANPSY PRIME team. It will involve developing and validating multi-agent approaches based on large language models (LLMs) applied to medical issues, such as creating diagnostic support tools from linguistic data and managing pathologies, generating interactive scenarios led by conversational agents, analyzing health data corpora, and designing predictive models for the progression of disorders. A challenge will be to ensure the robustness of LLMs to enable their use in complex and unpredictable human behavioral disorders, to ensure the reliability of models in clinical environments, and to participate in their validation with patients. The recruited person's project, while rooted in computer science, will need to be based on use cases developed in collaboration with clinicians at the site.

Host laboratories :

• Laboratoire bordelais de recherche en informatique (LaBRI - CNRS/Bordeaux INP/Université de Bordeaux)
• Sommeil, addiction et neuropsychiatrie (SANPSY - CNRS/Université de Bordeaux)

Being able to exploit massive imaging data in a clinical context is a major challenge in order to design, develop, evaluate and validate new approaches to analyze this data, with a much more integrated, transdisciplinary and translational vision. This involves integrating heterogeneous data and modelling patient care trajectories, including medical images, radiological reports, hospital and biological data. This should enable these multimodal data to be monitored longitudinally, in order to identify the factors that determine the effectiveness of treatments. The aim is also to identify and validate complex biomedical signatures from multimodal and multiscale sources (multi-parametric MRI, EEG, ECG, ultrasound imaging, biomolecular, genetic and phenotypic data, etc.), in order to reveal underlying pathological mechanisms and guide therapeutic approaches. To meet these challenges, the CNRS is offering a tenure track.

Host laboratories :

• Centre de recherche en acquisition et traitement d'images pour la santé (CREATIS - CNRS/Inserm/INSA Lyon/Université Claude Bernard Lyon 1)
• Laboratoire des sciences de l’ingénieur, de l’informatique et de l’imagerie (ICube - CNRS/Université de Strasbourg)
• Laboratoire recherche translationnelle et innovation en médecine et complexité (TIMC - CNRS/Université Grenoble Alpes)

This tenure track in machine learning for structural bioinformatics focuses on solving algorithmically complex problems with therapeutic applications. The project, centered on hybrid methods (AI, algorithms, physics, statistics), aims to model and characterize the conformational and dynamic properties of the most flexible biomolecules, such as disordered protein regions and coding or non-coding RNAs. The targeted properties include thermodynamic and kinetic behaviors, the impact of environmental conditions, the effects of post-translational modifications, and the prediction of interactions. The project seeks to address challenges related to the design of such molecules and their regulators in the medical field. To overcome limitations caused by the scarcity of data on these molecules, the project will leverage collaborations with experimental biophysics, in vitro biology, and biochemistry laboratories.

Host laboratories :

• Laboratoire d’analyse et d’architecture des systèmes (LAAS-CNRS)
• Laboratoire d’informatique de l’École polytechnique (LIX - CNRS/Institut Polytechnique de Paris)
• Laboratoire lorrain de recherche en informatique et ses applications (Loria - CNRS/Inria/Université de Lorraine)

Modeling and simulation of human behavior and interaction with robots are very active research topics at the interface of robotics, virtual reality and haptics, and extend from biomechanics to human motion analysis. Human-robot interaction is very rich in scientific problems that can be used to solve important practical robotic problems: role management between robot and human, multi-sensory feedback (visual, haptic), shared control algorithms to manage redundancy and the constraints of one or more robots, balance, motion planning. Added to this is the recent development in the field of machine learning methods, with the possibility of learning, imitating or reproducing human capacities for action and interaction with robots, by exploiting methods for synthesizing human movement, whether through kinematic or dynamic approaches.

Host laboratories :

• Institut de recherche en informatique et systèmes aléatoires (IRISA - CNRS/Université de Rennes)
• Institut des systèmes intelligents et de robotique (ISIR - CNRS/Sorbonne Université)
• Laboratoire d’analyse et d’architecture des systèmes (LAAS-CNRS)

The general objective of this project is to strengthen CNRS activities in the field of robotics, control engineering, and AI for autonomous systems interacting with humans, with two main research axes: developing new control approaches and architectures for autonomous vehicles taking into account human aspects, including the development of observers and estimators exploiting available data, and learning driving situations to adapt to driver preferences and constraints and enhance human driving capabilities in complex environments to improve safety and facilitate driving using technologies from robotics, autonomous systems, and artificial intelligence.

Perception and understanding of situations in open and dynamic environments, as well as vehicle uncertainty management and integrity, are major challenges addressed in this project, aiming to strengthen excellence laboratories in the field.

Host laboratories :

• Laboratoire Heuristique et diagnostic des systèmes complexes (Heudiasyc - CNRS/Université de technologie de Compiègne)
• Laboratoire d’automatique, de mécanique et d’informatique industrielles et humaines (LAMIH - CNRS/Université Polytechnique Hauts-de-France)