Mots-Clés

Translational, genomics/transcriptomics, oncology, statistics, machine learning

Description

The translational genomics research team (GeNeHetX) is seeking a motivated scientist interested in the development and transfer of transcriptomic signatures to improve the treatment of pancreatic cancer.

Pancreatic adenocarcinoma (PAC) is a highly aggressive form of pancreatic cancer with a five-year survival of around 10%. Chemotherapy is the only available form of systemic treatment for these cancers. The choice of chemotherapy is based on the patient's fitness rather than on the potential efficacy. The team has developed transcriptomic signatures to predict the benefit of specific chemotherapies based on each patient’s tumor phenotype. This has triggered in November 2022 a pioneering clinical trial in which the first line of chemotherapy is defined by a tumor RNA profile in pancreatic cancer.

The successful applicant will develop and/or apply disruptive technologies and methodologies to establish, improve and extend theranostic transcriptomic signatures. The work will be conducted in the GeNeHetX group (Translational Genomics of pancreatic Neoplasia Heterogeneity) of the INSERM research center on inflammation (CRI) in Paris. The successful applicant will work in a unique multidisciplinary environment, the team is composed of computational biologists in direct collaboration with the anatomopathological and clinical pancreatology departments of the Beaujon hospital (Clichy). The team gathers genomic data from multiple pre-clinical projects and clinical trials from France and EU.

The applicant’s work will contribute to the development of molecular signatures intended to be used in clinical practice to improve the care of patients affected by pancreatic cancer.

An ideal candidate would have a Ph.D. in Engineering, Biology, Statistics, Machine learning, Physics, or other related field and a strong interest in statistical and machine learning developments or applications to develop clinical-grade tools from genomic profiles.

Experience / Skills

• Experience working in a Unix environment and data analysis using R or python
• Basic knowledge in biology and statistics or machine learning is required

Contract duration: 12 months, renewable for 12 to 24 additional months.