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PhD (H/F) in multidisciplinary research: Physiopathology and mathematical data treatment

This offer is available in the following languages:
Français - Anglais

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General information

Reference : ERL5311-BEACOU-003
Workplace : TOULOUSE
Date of publication : Monday, June 29, 2020
Scientific Responsible name : Louis CASTEILLA
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 October 2020
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly

Description of the thesis topic

The ultimate goal of the overall project is to build a 3D numerical simulation model to identify, mimic and study the self-organizing endogenous mechanisms of post-traumatic or aging tissue reconstruction in adult mammals. The types of self-organization prevalent in a balanced adult tissue and in a tissue under construction are similar to the different phases of a physical system. Built on a functional, integrative and synthetic view, the project will rely on the combination of rule-based agent-type heuristic models with sophisticated imaging techniques. The models made as user-friendly as possible will be used to define a list of key determinants involved in triggering phase transitions and reaching a new state of equilibrium. Biological experiments will be conducted in the laboratory to calibrate the models and to test, validate and improve the underlying model assumptions using state-of-the-art methodologies, particularly in imaging and image processing. The validated hypotheses will be pharmacological targets likely to allow complete tissue regeneration or reversion of tissue degeneration that occurs during aging.

Work Context

The Stromalab team is internationally recognized for its expertise in regenerative medicine, based on the knowledge and use of mesenchymal stromal cells. The team has published the first trial on the use of adipose tissue stromal cells for the treatment of critical lower limb ischemia. It has set up a cell production process and a labelled quality control platform as part of the ECellFrance national infrastructure to ensure the safety and quality control of cells and in vivo biosafety testing of therapeutic cells. It has also demonstrated that adipose tissue is a physiological and therapeutic reservoir of stem cells that can be used in cell therapy. It has developed a highly original model of tissue regeneration in adult mammals that allows original hypotheses to be calibrated and tested (Labit et al, Scientific Reports, 2018). It highlighted for the first time biological questions that led to the first published mathematical model (Peurichard et al, J Theor Biol, 2019). It will provide longitudinal knowledge related to the processes of regeneration and rejuvenation.
The Imperial College team is interested in collective dynamics, decision making and self-organization in complex systems derived from biology and social sciences. The methods used combine analysis, asymptotic theory and multi-scale numerical techniques.

Bringing these two teams together will combine expertise in stem cell, stroma and tissue homeostasis biology with recent advances in modern data processing, making whole organ regeneration a realistic and achievable goal.

Constraints and risks

Regular travels between laboratories will be required.

Additional Information

Required profile : Master's student with a good background in applied mathematics and a strong interest in biology.
In particular, the candidate will have a good numerical background (programming under R and python) allowing him/her to be quickly autonomous in the implementation of the scientific developments planned.
He/she will also have good written and oral communication skills in both French and English. Exchanges and travels are planned with our English partners.
Recruitment : The recruited person will start his/her contract in October 2020. The application file will be made up of the following documents:
o Detailed curriculum vitae
o Copy of grades in M1, M2 and rank
o Letters of recommendation if applicable

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