Mots-Clés

Cancer biology single-cell RNAseq

Description

Context - Laboratories:

Institut Curie is one of the biggest European institutions for cancer research with a strong interdisciplinary tradition. It is located in the center of Paris, in a both cultural and scientific rich environment.

The Stress & Cancer team (https://curie.fr/equipe/mechta-grigoriou) headed by Dr. Mechta-Grigoriou is an internationally recognized laboratory investigating the impact of tumor heterogeneity in immunosuppression, metastatic spread and resistance to treatment. In particular, the lab has identified different cancer-associated fibroblast (CAF) populations in several cancer types, such as breast, ovarian and lung cancer and revealed that some specific CAF populations are involved in immunosuppression and resistance to immunotherapies. The lab recently generated an integrative high-resolution map of breast cancer by combining analysis of single-cell data, spatial transcriptomics and functional assays and uncovered spatial organization, plasticity and interactions of CAF populations with neighboring cells, including cancer and immune cells.

 

Project:

In this context, and in collaboration with the Data Science Department of Janssen (a pharmaceutical company of Johnson & Johnson), the lab of Dr. Fatima Mechta-Grigoriou is seeking a talented postdoctoral scientist with strong background in computational biology to analyze cell composition in ovarian cancer using data generated in this collaboration, and develop new methods where required to support this effort.

The project will be stratified in 3 main axes:

• Development of a single-cell atlas representative of the different cell types and states that compose ovarian cancer microenvironment.
• Deconvolution and analysis of bulk RNAseq data generated in the context of the project using the single-cell atlas developed in the first axis and perform compositional analysis of the patient samples with respect to available clinical parameters.
• Characterization of the tissue organization in ovarian tumors from multi-scale data integration (single-cell RNAseq, bulk RANseq, immunohistochemistry, clinical data)

Candidate Profile :

We are looking for a motivated and productive post-doctoral fellow.

Ideal candidate will have:

• A PhD in bioinformatics, applied mathematics or similar.
• Strong experience in handling high-dimensional -omics data and a keen interest to analyze complex heterogeneous biological data.
• Good programming skills (R, Python) and experience with good coding practices 
• Experience in machine /deep learning methods will be an additive value.
• Background in biology of cancer, immunology will be an additive value.
• Ability to be a team player, organized and curious, and able to drive the dynamics of the project.
• Great communication and writing skills.