14 rue Corvisart
Post-doctoral position in the field of computational biology applied to Pancreatic Cancer personalized therapy.
A postdoctoral fellowship for 18 months with possible extensions is available from January 2020 at the CIT program (Cartes d’Identité des Tumeurs) of the Ligue contre le cancer as part of the program "Personalized Medicine in Pancreatic Cancer" funded by The French National Cancer Institute (Inca).
This multidisciplinary project aims to propose new therapeutic strategies to personalize the management of Pancreatic Cancers using epidrugs, molecules targeting DNA methylation and histone modifications. The aim of this project is to describe and model the impact of epi-drugs on the phenotype of pancreatic tumors in order to propose personalized combinations of epigenetic and chemotherapeutic regimens.
From a collaboration with the team of Dr Iovanna (équipe Stress Cellulaire INSERM U.1068, Marseille), and based on a collection of more than 150 in vitro and in vivo models (PDX, cell lines and organoids) in association with their extensive molecular characterization (exome sequencing of normal and tumor tissue; CNV; methylome; ChIP-seq; mRNA RNA-seq transcriptome and miRNA), our team has defined molecular signatures predictive of chemotherapeutic response. An important subset of these models will be treated using a large panel of epi-drugs in order to compare their naive vs treated gene expression profiles.
The present project consists in modeling the impact of each epi-drug, in relation with their previously characterized chromatin state (5 histone marks in chipseq), and proposing methods to predict the phenotypic shift induced by each drug based on the initial molecular landscape. These signatures will then be validated on the rest of the series. The project will be accompanied by expert teams in the field of statistics (équipe statistique et génome, AgroParisTech) and of pancreatic physiopathology (équipe Stress Cellulaire INSERM U.1068, Marseille).
PhD and/or postdoctoral experience in computational Biology or applied statistics.
Candidates should have experience in the analysis of omics data, solid understanding of/knowledge in statistics and machine learning (supervised and unsupervised). Mastery of R in the Linux/unix environment is required as well as a solid mastery of handling large corpora of data. Experience in epigenetic and cancer biology is highly desired. Excellent communication and multitasking skills and ability to work in a team setting is required.
A resume with list of publications accompanied by a letter of motivation and at least one letter of recommendation should be addressed to:
Remy Nicolle firstname.lastname@example.org and Yuna Blum email@example.com.