The position will take place in the environment of the team COMPO (COMputational Pharmacology in Oncology). The team is jointly affiliated to Inria and the Center for Research on Cancer (CRCM, Inserm, CNRS, Aix-Marseille University). It is composed of mathematicians, data scientists, pharmacists and clinicians and is a unique multidisciplinary environment focused on developing novel computational tools for decision-making in clinical oncology. 

The successful candidate will work in close collaboration with high-level scientific teams and the bioinformatics platform at the CRCM. It is a 4-years contract with attractive salary leading to a full Professor position conditionally to research achieved.

Description

The generalization of new generation sequencing data (i.e., multi-omics: genomics, transcriptomics, proteomics,…) as well as the emergence of new methods (single cell sequencing, spatial transcriptomics) opens new research horizons on cancer pathologies. These data, of very large dimensions and volume, bring new methodological challenges in terms of statistical and mathematical analysis, as well as computational modeling. The development and numerical implementation of these methods has become a key issue in modern oncology, both in terms of understanding the biology of cancers and for medical oncology. On the first aspect, the analysis and modeling of these data is, for example, fundamental for the study of key phenomena such as intra- and inter-tumor heterogeneity of cancer cells and their microenvironment. On the other hand, the integration of multi-omics data into predictive artificial intelligence models will allow the development of precision medicine based on personalized treatments.

We are looking for a strongly motivated candidate with high-level track record of computational research for omics data.

Salary

3 443€ minimum, adjusted on the candidate’s experience.

Start-up package: 200k€

Contact:

sebastien.benzekry@inria.fr https://team.inria.fr/compo/ https://www.crcm-marseille.fr/ To apply: https://galaxie.enseignementsup-recherche.gouv.fr/antares/can/astree/index.jsp