PhD Position (M/F) in Generative Artificial Intelligence for Modeling Protein Flexibility

Job Description

Thesis Subject

Intrinsically disordered proteins and intrinsically disordered regions (IDRs) play essential roles in many biological processes. Unlike conventional proteins, they do not adopt a single stable structure but instead populate a wide range of conformations. This structural flexibility is closely linked to their biological function but also makes them particularly challenging to study and model.
The objective of this PhD project is to develop novel artificial intelligence methods capable of predicting conformational ensembles of intrinsically disordered proteins directly from their amino acid sequences. The project will build upon recent advances in deep learning, particularly flow-matching generative models and protein language models.
The research will focus on designing efficient generative models able to produce realistic conformational ensembles while integrating knowledge from statistical physics and structural biology. The developed methods will be evaluated using both computational reference data and experimental measurements obtained through collaborations with biophysics laboratories.
The project lies at the intersection of artificial intelligence, machine learning, computational physics, and molecular biology, and aims to contribute new methodological foundations for the study and design of flexible biomolecular systems.

Expected Skills
• Master's degree or engineering degree in computer science, artificial intelligence, applied mathematics, computational physics, or a related field;
• Strong background in machine learning, probability, and statistics;
• Proficiency in scientific programming with Python and deep-learning frameworks such as PyTorch;
• Interest in generative modeling and modern AI methods;
• Motivation to work at the interface of artificial intelligence, statistical physics, and molecular biology;
• Good scientific communication skills in English;
• Curiosity, autonomy, rigor, and ability to work in an interdisciplinary research environment.

Your Work Environment

The PhD project will be carried out within the RIS team at the LAAS-CNRS laboratory in Toulouse, France. The candidate will work in a multidisciplinary research environment involving expertise in artificial intelligence, applied mathematics, and computational biology.
The project includes collaborations with academic partners specialized in probabilistic modeling and experimental biophysics, notably through interactions with research groups in Paris and Montpellier. The candidate will benefit from access to the laboratory's scientific computing resources and the broader CNRS research ecosystem.

Constraints and risks

The work will be primarily computer-based and conducted in a standard office and research environment. No specific occupational risks have been identified.

Compensation and benefits

Compensation

2300 € gross monthly

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

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