Profil Recherché

Titulaire d’un doctorat ou diplôme équivalent ou justifiant de titres et travaux scientifiques jugés équivalents par l’instance compétente de l’établissement. Il n’y a aucune condition d’âge ou de nationalité pour candidater. Tous les emplois CNRS sont accessibles aux personnes en situation de handicap en bénéficiant d’aménagement d’épreuves rendus nécessaires par la nature du handicap

Stratégie d'établissement

Multidisciplinarity is one of the strengths of the CNRS, enabling the mobilization of high-level researchers across all fields of modern experimental science.
In the project proposed for this CPJ, the goal is to develop computational approaches to address methodological challenges raised by issues in biology and health. This is particularly relevant in the context where methodologies associated with generative AI are currently revolutionizing the field of molecular modeling and simulation (e.g., structural biology), enabling advancements in the understanding of intracellular mechanisms and accelerating the development of therapeutic solutions.
This CPJ is part of a broader series of initiatives at the interfaces between computer science, mathematics, biology, chemistry, and health, aiming to develop a national ecosystem of researchers from various disciplines, capable of tackling the key computational challenges related to analysze biology and health data, spanning fundamental research to translational applications.
The CNRS, through its strategic plan (COP), promotes interdisciplinarity, and this CPJ aligns with this objective, particularly around the themes of AI for the sciences (and reciprocally).

Stratégie du laboratoire d'accueil

Three laboratories have been identified for this position, combining fundamental research in computer sciences with strengthened collaborations in chemistry, biology, and/or health.
These three laboratories (LAAS, LIX, and LORIA) host renowned researchers in computer science applied to the prediction and modeling of molecular structures, particularly RNA, proteins, and their complexes. They work closely with experimental laboratories to develop state-of-the-art molecular prediction algorithms, with applications in biology and health.
This CPJ (Junior Professor Chair) aims to strengthen the involved teams by recruiting ax expert in interpretable or deep machine learning, to enhance interdisciplinary collaborations and improve the understanding of molecular structure properties that remain unresolved by the latest techniques.

Stratégie Internationale

CNRS welcomes and recruits a large number of international researchers. More than 30% of those recruited come from abroad. This recruitment will have the same ambition.

Répertoire national des structures de recherche (RNSR) du laboratoire d'accueil

199517454Y
200519331V
198912571S

Résumé du projet scientifique

This CPJ 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.

Résumé du projet d'enseignement

The teaching activities of the recruited person will align with the teaching strategy of the associated sites through their specialized programs in computer science at the interfaces with health, biology, and biochemistry fields.

Environnement Financier

• Total financé (dont package ANR) : 200 k€
• Total du projet : k€

Diffusion scientifique

The dissemination of the results will be done through world-class scientific productions: publications, patents, software... In addition, the results will be communicated to various targets such as scientific communities, media, decision makers, general public, schools, etc., with an adapted calendar. Specific tools may be developed such as websites, newsletters, meetings, international symposia, summer schools and conferences.

Science ouverte

The CNRS is developing a strong policy in favor of open science. Open science consists of making research results "as accessible as possible and closed as necessary". As such, the CNRS aims to make 100% of the texts of publications resulting from the work of its laboratories accessible , in particular through deposit in HAL. The data produced must also be made available and reusable, except for specific restrictions. In addition, the guiding principles of individual evaluation have been revised in accordance with the DORA declaration, to be more qualitative and to take into account all facets of the researcher's profession.

Science et société

The relationship between science and society is now recognized as a full dimension of scientific activity. The project will develop this dimension in synergy with all the partners. The resulting research work will contribute to informing public decision-making. Participatory science initiatives may be initiated with actors from the project’s socio-economic and cultural eco-system.

Indicateurs

The activity will be evaluated in particular on the basis of scientific production (publications, software, patents, etc.), on institutional and private partnerships formalized by contracts, on international presence, on the promotion of work to multidisciplinary scientific communities, on innovation and its transfer to society and on scientific dissemination to non-specialist audiences.

Modalités d'organisation des auditions

Seul(e)s seront convoqué(e)s aux auditions les candidat(e)s sélectionné(e)s sur dossier par la commission de sélection