Model fish species (e.g. zebrafish, medaka, fathead minnow) are largely used to study the impact on the reproductive function of environment perturbations, such as climate change or exposure to pollutants, whether it be on the individual or population scale (ecophysiology/ecotoxicology). The maturation process of gametes (oocytes) in females is indeed particularly sensitive to internal (e.g. metabolic status) and external (temperature, salinity, endocrine disruptors) environment factors. Moreover, this process is a key point to control the reproductive fitness. Yet, to date, the fitness is assessed through rather rough indicators that mostly account for the final output of the gametogenetic process, the spawning performances.

In the framework of a collaboration between the  lab Physiologie de la Reproduction et des Comportements (Centre INRAE Tours), the team MUSCA (Inria Saclay Île de France) and the lab Physiologie et Génétique des Poissons (Centre INRAE Rennes), we aim to develop a model of fish oogenesis accouting for the main stages and checkpoints targeted by environment and physiological controls, and enabling one to represent the whole oocyte dynamics from the earliest stages, in addition to the spawning size and frequency.

The thesis includes three modeling approaches, ODE, PDE and multi-scale modeling, each of which responds to different issues.

The student will join the BIOS team within the lab Physiologie de la Reproduction et des Comportements (PRC, INRAE Tours) and will
continuously interact with the lab Physiologie et Genetique des Poissons (LPGP, INRAE Rennes) where the experiments and data acquisition are performed. In addition, the student will join the joint INRIA-INRAE-CNRS Musca team, of which the members of the BIOS team are part. The Musca team is specialized in multi-scale modeling in physiology, and will provide an ideal framework for the methodological support of the student.

The profile sought is in applied mathematics, biomathematics (Master's degree in biomathematics or engineering school applied mathematics course) with solid knowledge in ordinary differential equations and partial differential equations. Knowledge of statistics and/or stochastic processes will be appreciated.

This is an interdisciplinary thesis, with the acquisition of strong skills in mathematical modeling of population dynamics, numerical simulation, and statistical inference. The student will also become familiar with concepts of physiology, acquisition and processing of biological data. These broad skills will be an asset for the promotion of the future career of the student.

Please contact Romain Yvinec (romain.yvinec@inrae.fr) for application details.