Lead researcher position : Computational modeling for multi-omics data

French National Institute for Health Research (INSERM); Marseille; Sur place; EUR 40 000 - 70 000; Plein temps

Résumé du poste

An established industry player is seeking a motivated individual to join their team as a junior researcher focused on cutting-edge computational methods in cancer research. This role involves leveraging multi-omics and single-cell resolution data to drive innovative discoveries, addressing key challenges in statistical analysis and computational modeling. Collaborating with multidisciplinary teams, you will contribute to the advancement of precision medicine through the integration of advanced data analysis techniques. If you're passionate about making a difference in oncology, this opportunity offers a dynamic environment to grow and excel.

Qualifications

• Experience with multi-omics data analysis and computational methods.
• Strong background in statistical modeling and machine learning techniques.

Responsabilités

• Develop computational methods for analyzing multi-omics data in cancer research.
• Integrate predictive models to enhance precision medicine approaches.

Connaissances

Statistical Analysis

Computational Modeling

Data Integration

Machine Learning

Formation

Master's in Bioinformatics

PhD in Computational Biology

Outils

R

Python

Bioconductor

Description du poste

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 novel 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 are, 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.

This junior chair position aims to develop cutting-edge computational methods to leverage multi-omics and single-cell resolution data into novel and translational discoveries in cancer research. This will be performed in synergistic interaction with the other CRCM teams.