Main tasks

Laboratory

The Cavalli Lab is part of the "Computational Oncology" Unit (U1331 INSERM, Mines ParisTech, Institut Curie) at Institut Curie, which consists of ~90 researchers and students. It is a very active and growing interdisciplinary team of bioinformaticians, biologists, physicians, mathematicians, statisticians, physicists, and computer scientists (U1331 Unit page).

The Cavalli Lab (located at Institut Curie St-Cloud, west of Paris), investigates tumor heterogeneity, targeting clinically relevant questions. The goal of our genomic approaches is to explore clinically relevant aspects of brain tumor biology. We pursue this goal using patient samples profiling, investigating temporal and intra-tumoral/spatial heterogeneity as well as tumor/tumor microenvironment interactions in gliomas and pediatric embryonal brain tumors. Projects in the Cavalli lab are developed within a dynamic and collaborative environment with other researchers and clinicians at Institut Curie and national/international wet lab collaborators.

The project

We seek a talented individual to tackle the complexity of tumor biology and intra-tumoral heterogeneity performing computational analysis of cutting-edge sequencing datasets. S/he will be in charge of the analysis of single-nucleus RNA/ATAC-seq and spatial transcriptomics data from brain tumor patient samples or models in close collaboration with experimentalists.

This project focuses on deciphering tumor cell plasticity, including method evaluation/development and biological interpretation of the results. In addition, s/he will drive a cross species pediatric tumor model comparison deciphering tumor cell programs. Finally, s/he will investigate the metabolome of IDH-mutant glioma tumors and perform data integration with omics layers to further decipher treatment resistance mechanisms.

Responsibilities

-        Drive and develop scientific projects focused on tumor heterogeneity

-        Perform end-to-end data analysis (QC, processing, visualization, interpretation…)

-        Analyze single-cell and spatial transcriptomics datasets

-        Decipher metabolomic patterns

-        Perform high dimensional data analysis and integrative ‘omic’ data analysis

Candidate Profile

Training and Skills required

-        (Recent) PhD in bioinformatics, statistics, or computer science with knowledge and interest in biology

-        Track record of creativity in developing analytic strategies

-        Strong foundation of knowledge in one or more of the following: genomics, cancer biology, statistics

-        Experience working in a Unix environment and statistical analysis using R

-        Excellent computational biology skills

-        Experience with single-cell RNA-seq analysis

-        Experience with machine learning based methods

-        Have evidence of scientific accomplishment via peer-reviewed publications

-        Understanding of cancer cell biology is an asset as well as experience of collaboration with biologists for solving concrete biological problems

Abilities

-        Must be self-motivated, capable to work in autonomy

-        Excellent written and verbal communication skills in English

-        Capacity to communicate with oncologists and biologists

-        Critical thinking

-        Team spirit is essential

All our opportunities are open to people with disabilities