A 3 year post-doctoral position dedicated to the development of personalized medicine for Pancreatic Cancer is available in the "Pancreatic Cancer" team at the Cancer Research Center of Marseille in France, under the supervision of Dr. Nelson Dusetti and Dr. Philippe Soubeyran.
Pancreatic adenocarcinoma (PDAC) is one the most aggressive form of cancer and is becoming a serious health problem as its incidence increases constantly. The main cause of death in PDAC is recurrence due to innate or acquired chemoresistance. Despite relative efficacy of therapies, a majority of tumors progress despite continued treatment, strongly suggesting the presence of chemotherapeutic-resistant cells in the tumor prior to treatment or the ability of some tumor cells to acquire resistance induced by treatment.
The project, funded through the ARC (Association pour la Recherche sur le Cancer), will aim at studying and understanding the role intra-tumor heterogeneity and of its evolution during treatments at the cellular level. This will allow us to predict drug sensitivity of the different cell populations constituting the tumor before the treatment thereby offering individualized and appropriate therapies to each patient, sparing from toxicity of inefficient treatments.
To proceed, we will use single cell RNA sequencing combined with cell lineage tracking in order to highlight the different mechanisms that drive the acquisition of the chemo-resistant phenotype at the individual cellular level. We will use this knowledge to identify predictive signatures of sensitivity and/or future acquisition of chemo-resistance.
The candidate will have to identify molecular signatures and to validate them on independent cohorts of patients. This project will be accompanied by expert teams in the field of bioinformatics. The candidate post doc will also participate to the development of novel strategies involving single cell RNAseq methodologies (SPLiT-seq) to gain insight into implication of intra-tumoral heterogeneity in treatment resistance. Consequently, candidates should have experience in the analysis of RNA-seq data, including of raw sequencing process, as well as good general knowledge in statistics and machine learning (supervised and unsupervised). Mastery of R in the Linux environment is required as well as a solid mastery of handling large corpora of data. Experience in single cell analyzes would be appreciated.
A CV with list of publications accompanied by a letter of motivation and 2 recommendation letters should be addressed to Nelson DUSETTI firstname.lastname@example.org and Philippe Soubeyran email@example.com