JOIN THE CRCT

Where ?

A 2-year post-doctoral position is available in the DIAD team (Dose Individualisation of Anti-cancer Drugs) part of the Center for Research in Cancer Toulouse (CRCT, UMR 1037, Inserm, https://www.crct-inserm.fr/en/) co-supervised by Etienne Chatelut, Melanie White-Koning and Jean-Baptiste Woillard (from University of Limoges).

What?

The position has been created as part of the DIGPHAT project, funded by the French government (PEPR Santé numérique) which includes several teams from several universities and research bodies in France.

The DIGPHAT (Digital Pharmacological Twins) Project (https://anr.fr/ProjetIA-22-PESN-0017)  is interested in collecting and modelling pharmacological and multimodal data at different scales: molecular (identification of drug action mechanisms), cellular (e.g. characterisation of tissues lesions), patient (pharmacokinetics /pharmacodynamics population variability).  A multidisciplinary consortium with expertise in pharmacology, integrative genomics, and mechanistic or AI-based modelling is working on tackling these challenges and aims to develop a computational framework allowing the integration of an ensemble of data driven and mechanistic models into meta-models through either Bayesian networks or artificial intelligence (AI) approaches. These meta-models will improve the prediction performances in terms of personalization of drug therapies (choice of molecule, dose, concentration targets and associated regime) in clinical practice as well as evaluating their adverse effects. This project aims to generate digital pharmacological twins which will be applied to 3 major clinical areas: renal transplantation, oncology and resistant bacterial or fungal infections.

The role of the recruited post-doc will be to focus on the oncology applications (renal and lung cancer) and participate in work packages 3 and 4 of the project, collaborating with other colleagues from the consortium with the following aims:

• assess the relevance of computational models for the different biological scales and refined mechanistic PK or PK/PD models selected from the literature, by implementing them and simulating profiles based on these models.
• aggregate different types of multiscale models (mechanistic or machine learning) to predict the probability of clinical events. Encoder and transformers will have to be adapted to overcome some challenges such as mixing basal and longitudinal covariates, capture dependencies in sequential data. Deep learning model allowing to integrate both ODE and data-driven approaches (including neural ODE in the original scale or latent space) will be developed. The data used will be published/simulated data together with existing available data from the different teams involved in the project.

Who?

The ideal candidate will have strong expertise and experience in machine learning, deep learning, preferably with applications in the pharmacology, biology or medical fields.

Required qualifications and professional skills

• PhD in any of the following: mathematics, biostatistics, bioinformatics, computational biology, computer science, pharmaceutical and/or medical sciences with experience in AI or other relevant discipline.
• Strong experience in machine learning, deep learning, big data analysis.
• Knowledge of/experience in pharmacology/pharmacometrics would be an asset but is not required.

Soft skills: Excellent skills in communication, creative problem-solving, teamwork.

REQUESTED DOCUMENTS OF APPLICATION, ELIGIBILITY CRITERIA, SELECTION PROCESS

• A curriculum vitae
• A concise presentation of the current research
• The name and email addresses of three referees

HOW TO APPLY:

by email to both chatelut.etienne@iuct-oncopole.fr AND melanie.white-koning@univ-tlse3.fr

TYPE OF CONTRACT: TEMPORARY JOB STATUS: FULL TIME

ENVISAGED STARTING DATE: 01/05/2025
ENVISAGED DURATION: 48 months

WORK LOCATION(S): Based in Toulouse (Center for Research in Cancer Toulouse (CRCT, UMR 1037, Inserm), 2 avenue Hubert Curien, 31000 Toulouse) with some travelling for short periods of time (a few days) to other locations in France (e.g. Limoges, Marseille)