Build prognostic models of treatment response and survival based on multi-omics approaches

Type de poste
Niveau d'étude minimal
Dates
Durée du poste
Contrat renouvelable
Contrat non renouvelable
Date de prise de fonction
Date de fin de validité de l'annonce
Localisation
Adresse

114 RUE EDOUARD VAILLANT
94800 VILLEJUIF
France

Contacts
Caroline ROBERT
Sergey NIKOLAEV
Daniel GAUTHERET
Email du/des contacts
Caroline.ROBERT@gustaveroussy.fr
Sergey.NIKOLAEV@gustaveroussy.fr
daniel.gautheret@universite-paris-saclay.fr
Description

A 2 to 3 years postdoctoral position is available immediately for a computational biologist at INSERM UMR 981 (group of Pr Caroline ROBERT). The candidate will work on transcriptomics and genomics of malignant melanoma in the field of immuno-oncology. She/he will develop multi-omics approaches, in order to identify biomarkers of resistance and sensitivity to immunotherapy. The goal is to build prognostic models of treatment response and survival based on RNA-seq and integrating information about driver mutations, mutational signatures and other omics data.

The prospective trial will be instrumental to achieve this goal, offering biopsies before immunotherapy to uncover genes and pathways that could serve as biomarkers of treatment success. Our RNA dataset is unique in that libraries are prepared for total RNA sequencing, enabling observation of non-coding transcripts, whose role in cancer is currently understudied. Afterwards the candidate will integrate transcriptomic data in the context of genomic, epigenetic and proteomic variation.

This rare combination of clinical expertise and omics data available at Gustave Roussy is a unique opportunity for a postdoctoral scientist to make a real difference in the future treatment of melanoma patients.

Keywords: cancer, melanoma, RNAseq, WES, immunotherapy

 

Applicant’s profile

- Strong scientific track record (international publications and communications)

- Robust experience with RNAseq and WES analysis;

- Biological knowledge in immuno-oncology

- Programming skills in python, R

- Knowledge in statistics

- Ability of collaborative team work and autonomous work

- High motivation and interest in systems and computational biology

- Fluency in English

 

Application

- Curriculum vitae (including list of publications and communications)

- Motivation letter describing previous experiences and reasons underlying the application

- Contact information for referees or previous mentors

 

Equipe adhérente personne morale SFBI
Equipe Non adhérente