DESCRIPTION :
This post-doctoral position is in the frame of the ANR project ENERGENCE headed by D. Peurichard (Inria Paris, MUSCLEES team) and our biological partners at RESTORE, Toulouse. The long lasting collaboration between the two partners led to the development of mathematical models for adipose tissue development and morphogenesis [Peurichard et al, JTB, 2017], [Chassonery et al, RSOS, 2024] and was extended to study AT reconstruction abilities after injury [Peurichard et al, JTB, 2019]. In both studies, it proved to be an invaluable tool to highlight the key role of mechanical interactions in AT, and enabled to identify a new therapeutic target to induce regeneration in scarring tissues, validated in-vivo [Pacary et al, Nat Reg Med, 2024]. Therefore, these models represent an important proof-of concept that mechanical interactions could be a major driver of tissue architectures. However, in their present state the developed models do not take into account energy exchanges/metabolism, as
biological phenomena (cell growth, insemination, matrix crosslinking) are prescribed by some growth laws not linked to external energy arrivals nor to mechanical constraints. The goal of this project is therefore to take a step further and introduce metabolic considerations into the mechanical model to reach a complete model for tissue architecture emergence, enabling to study the role of mecano-chemical feedback loops in tissue equilibria, repair and ageing.
The post-doctoral candidate will develop and analyze agent-based models (ABM) to explore and determine the complex feedback loops between energy intakes and local growth laws, and study how the tissue architecture evolves as a result of changes in energy fluxes, modelling cafeteria diet and food deprivation. The parameters of the constructed ABM will be calibrated on experimental measurements at RESTORE and the model results will be systematically confronted to experimental data from the litterature and generated by our biological partners.
The post-doctoral fellow will be located at LJLL, Sorbonne University, with regular visits to the RESTORE lab in Toulouse. Travel expenses will be covered by the projects.
Mission confiée
The recruited person will use the 2D and 3D spatial models developed in the team -featuring mechanical interactions between adipocyte cells and cross-linked fibers- as a starting point [Peurichard et al, JTB, 2017], and implement new rules to account for nutrient- and mechanically-limited growth laws. This task will be highly interactive, since the choice of a convenient model is both critical and the very first key point. It will be performed via constant interactions with the biological partner. This step will validate the choice of growth laws and energetical feedback loops, and may lead to an adaptation of the model hypothesis.
The recruited person will perform numerical simulations to study the new behaviors / tissue architectures that emerge from the new model, and the influence of these newly defined feedback loops between energy and mechanics in the equilibrium structures. The fine-tuning and validation of the newly developed model will rely on a quantitative comparison with experimental images generated at the RESTORE lab. The complete model will be analyzed by a systematic sensitivity analysis of the free model parameters to better understand how they control model outputs described by a set of quantifiers. With the help of D. Peurichard and informaticians at the RESTORE lab, the candidate will develop new unsupervised sensitivity analysis tools at the intersection between machine learning and ABM.
Depending on the first results and on the software competences of the recruited person, a user-friendly interface will be developed based on the ABM, to be transferred to the RESTORE lab and used to explore how the AT architecture is modified by the amplitude, frequency and length of energy intake modifications., * Development of agent-based models and numerical implementation of the models (python, C++, Fortran90 ...)
* Analysis of the models (sensitivity analysis combining classical and machine learning tools)
* Development of image processing tools and appropriate quantifiers for confrontation model/ data
* Maintaining regular interactions with biological collaborators
* Writing reports/papers
Additional activities (according to the candidate preference) :
* Development of a user-friendly software and transfer to the biologist lab
Code d'emploi : Chargé de Recherches (h/f)
Domaine professionnel actuel : Scientifiques
Niveau de formation : Bac+8
Temps partiel / Temps plein : Plein temps
Type de contrat : Contrat à durée indéterminée (CDI)
Compétences : C ++ (Langage de Programmation), Données Expérimentales, Python (Langage de Programmation), Machine Learning, Programming Languages, Sens de la Communication, Compétences Interpersonnelles, Convivialité, Esprit d'Équipe, Implication et Investissement, Motivation Personnelle, Algorithmes, Mathématiques Appliquées, Architecture, Biologie, Croissance Cellulaire, Métabolisme, Nutrition et Diététique, Physique Informatique, Marketing, Traitement d'Image, Modélisation Mathématique, Mesure et Métrologie, Sciences Physiques, Recherche Post-Doctorale, Processus Stochastique, Analyse de Sensibilité, Rédaction de Rapports, Compétences de Modélisation, Capacités de Démonstration
Courriel :
diane.a.peurichard@inria.fr
Téléphone :
0139635511
Type d'annonceur : Employeur direct