Job offer

The successful candidate will work on the development and calibration of a generic multi-scale model incorporating publicly available omics data.

• Develop Boolean and agent-based models.
• Develop coupling methodologies for large-scale hybrid models.
• Conduct sensitivity, robustness and scalability analyses.
• Integrate multimodal cohort datasets.
• Apply machine learning approaches for prediction and stratification.
• Develop software.

Le projet DigiTREAT, financé par le programme PEPR Digital Health, vise à développer un jumeau numérique multi-échelle pour la polyarthrite rhumatoïde (PR) en intégrant la modélisation computationnelle, les données omiques et les cohortes cliniques. Le projet répond à un besoin clinique majeur non satisfait : prédire la réponse au traitement dans les maladies auto-immunes complexes. The DigiTREAT project, funded by the PEPR Digital Health programme, aims to develop a multi-scale digital twin for rheumatoid arthritis (RA) by integrating computational modelling, omics data and clinical cohorts. The project addresses a major unmet clinical need: predicting treatment response in complex autoimmune diseases. The position is based at the Centre for Integrative Biology (CBI) in Toulouse, a joint research centre of the CNRS and the University of Toulouse III - Paul Sabatier dedicated to integrative biology at all scales. The successful candidate will join the Systems Biology Division and will be supervised by Professor Anna Niarakis. https://cbi-toulouse.fr/en/equipe/pole-de-biologie-des-systemes-en/ The post falls within a sector subject to the protection of scientific and technical potential (PPST) and therefore, in accordance with regulations, requires your arrival to be authorised by the competent authority at the MESR.

PhD or equivalent

Research Field Physics

Education Level PhD or equivalent

Research Field Biological sciences, Qualifications : PhD in bioinformatics, computational biology, applied mathematics or a related field Skills : Expertise in modelling biological systems (Boolean models, ABM or equivalent). Experience in machine learning and data integration. Strong programming skills: R, Python (C++ desirable). Proven track record of publications. Personal qualities : rigour, ability to report findings.