Université Grenoble Alpes
We are seeking a highly motivated post-doc with a PhD in bioinformatics, biostatistics, computer science, mathematics or epidemiology (TIMC-IMAG UMR5525, BCM group, duration: one to four years, starting january 2020).
Work Context: This work is part of a research grant from the « Institut National du Cancer » and the « Institut de Recherche en Santé Publique » that conducts in vitro experiments and compare the expected data with the dataset from placenta samples in order to identify the molecular basis of cigarette smoke-induced epigenetic alterations, their inheritability and their functional consequences.
The project will use complementary approaches combining a concept-driven analysis with an Epigenome-Wide Association Study (EWAS) to identify CpGs and differentially methylated regions associated with post-conceptional and pre-conceptional maternal smoking. Mediation-EWAS models (multi-mediator models) will be developed and investigated in order to provide accurate identification of multiple mediators and estimation of direct and indirect effects of maternal smoking on birth weight. We will apply causal analysis, machine learning and latent variable methods to characterize causal and confounding factors. The objective of the project is to better understand the relationship between a high-dimensional set of causal markers and maternal smoking and offspring birth weight for our cohort data. Depending on the post-doc's interests, there is plenty of opportunity to add elements to the project, a larger epidemiological component, a modeling dimension, methylation experiments, etc
Profile: Applicants should have expertise in handling genomic or epigenomic data, and have strong statistical and computer skills. An interest in genetic epidemiology and maternal smoking would be a plus.