Post-Doctoral position - "Computational modelling of vascular aging conditions"- CDD 18 months
Confidential
Posted: April 10, 2026
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Quick Summary
Joining Mines Saint-Étienne means committing to an institution where science and innovation build a more sustainable future. The ideal candidate will have expertise in computing and modeling of vascular aging conditions, and be able to work collaboratively with researchers and students.
Required Skills
Job Description
Joining Mines Saint-Étienne means committing to an institution where science and innovation build a more sustainable future. It is a school of excellence where everyone has the opportunity to unlock their full potential and contribute to tackling the challenges of tomorrow.
Ranked among the top engineering schools in France and recognized worldwide, our school, a member of the Institut Mines-Télécom, educates the talents of tomorrow while actively addressing major industrial, digital, and environmental challenges. By joining us, you become part of a community of 500 members of staff, 2,500 students and take part in an ambitious project: combining academic excellence, cutting-edge research, and positive societal impact.
The Institut Mines-Télécom brings together France’s leading Grandes Ecoles to tackle major industrial, digital, energy, and environmental challenges. With its eight public Grandes Écoles and two affiliated Graduate Schools, it is the leading public institute dedicated to engineers and managers. Together, we imagine and build a sustainable future by educating the leaders who will shape tomorrow’s transitions.
🎯 What we expect from you
As post-doc, you will be at the heart of our missions in research and innovation, assigned to the SAINBIOSE lab. SAINBIOSE (INSERM UMR 1059) brings together researchers from Mines Saint-Etienne (biomechanics, biomaterials and bioengineering), the faculty of Medicine from Jean Monnet University, Saint-Etienne University Hospital, Inserm and the French Blood Establishment. The global scientific objective of SAINBIOSE is a better understanding and of biostress in osteoarticular (LBTO team) and cardiovascular pathology (DVH team).
Website: https://sainbiose-lab.fr/
Biomechanics, experimental and computational, is a major research topic of SAINBIOSE, which goes from modelling the mechanical behaviour of tissues to clinical and industrial applications, especially with the textile industry. In 2024, Prof Stéphane Avril was awarded an ERC Advanced grant from the European Research Council for the project JuvenTwin “Multiscale mechanobiological synergies in vascular homeostasis, ageing and rejuvenation”, which aims to establish multiscale digital twins of ageing effects on vascular mechanobiology and to simulate and screen effective rejuvenation treatments. This project will take place in a research group having 15 years experience in biomechanics and mechanobiology (https://emse.fr/~avril/).
We open a non-permanent position of post-doctoral fellow to join the Avril’s team working on JuvenTwin’s project. The work will be carried out at Mines Saint-Etienne, within the SAINBIOSE research unit (Inserm U1059). It is based at the Centre Ingénierie et Santé (Hospital campus at the North of Saint-Etienne).
The objective of the post-doctoral fellow will be to develop an innovative computational models (multi-scale digital twin, machine learning, growth and remodeling) in which we will calculate deformation fields using a combination of traditional finite-element model and physics informed neural network for realistic microstructures of arterial extracellular matrix (reconstructed from patient-specific micro-architectures) in which a large population of prestressed cells will be embedded. Temporal variations of cell prestress in the model will be informed from the patient-specific data of collaborators in the JuvenTwin project and using a computational model of cell signalling networks.
Your ability to work in a project-based environment and to create links between teaching, research, and practical applications will be essential for success.