Job offer

CNRS
Villeurbanne, France
1 day ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Computer Simulation Computer Programming Image Analysis Experimental Data Python (Programming Language) MATLAB Machine Learning Scientific Computating Claude

Job description

The PhD project will focus on the development and analysis of multi-tissue mathematical models of embryogenesis, based in particular on systems of partial differential equations arising from fluid mechanics.

The main objectives will be:

  • Develop and analyze mathematical models describing the dynamics and interactions between multiple tissues during embryonic development
  • Investigate analytical questions associated with these models, including their qualitative behavior and the influence of model parameters
  • Implement numerical methods adapted to the systems under consideration
  • Develop methods to connect the models with experimental data and estimate relevant model parameters
  • Compare theoretical and numerical results with imaging data, using image-processing and machine-learning tools when appropriate, The PhD is part of the interdisciplinary PREMMOVE project (2025-2031), funded by the PEPR Maths-Vives program. It will be co-supervised by Michèle Romanos (CR CNRS) and Simon Masnou (Professor, Université Claude Bernard Lyon 1).

Keywords: morphogenesis, mathematical modeling, partial differential equations (PDEs), PDE analysis, numerical simulation, artificial intelligence, image analysis.

Requirements

Master’s degree in mathematics or applied mathematics, with a strong background in analysis, partial differential equations, and numerical methods

  • Good skills in scientific computing and programming, particularly in Python, Julia, or Matlab
  • Strong interest in mathematical modeling and interdisciplinary research, particularly at the interface with biology
  • Previous experience in mathematical modeling, as well as knowledge of continuum mechanics or machine learning, would be appreciated

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