Mots-Clés

Boolean models data integration colon cancer

Description

Links

http://curie.fr, http://u900.curie.fr http://sysbio.curie.fr, https://prairie-institute.fr/

Context

Institut Curie is one of the biggest European institutions for cancer research with strong and old interdisciplinary traditions. It also comprises a hospital specialized in cancer treatment, and therefore dispose of a continuum of expertise from fundamental research to patient care. It is located in the centre of Paris in a both cultural and scientific rich environment (http://curie.fr).

The "Bioinformatics and Computational Systems Biology of Cancer" Unit (U900 INSERM, Mines ParisTech, Institut Curie) involves about 110 researchers and students. It is a very active and growing interdisciplinary team of biologists, physicians, mathematicians, statisticians, physicists and computer scientists (http://u900.curie.fr). Our research group Computational Systems Biology of Cancer focuses on deciphering determinants of tumorigenesis and tumor progression and proposing new strategies to combat cancer. The domains of expertise are big data analysis; single cell data analysis; patient stratification; signaling network construction and mathematical modeling; study of synthetic interactions in cancer mechanisms, drug response prediction and many others (http://sysbio.curie.fr). The group has strong expertise in application of machine learning, mathematical modeling to cancer omics data aiming at solving important clinical problems (https://sysbio.curie.fr/publications.html). Two members of the group hold chairs of Paris of Artificial Intelligence Research Institute (https://prairie-institute.fr/). The group has also long-term experience in implementing scientific methodology of data and biological network analysis into user-friendly software, currently used by other researchers world-wide (the list of developed software can be found at http://sysbio.curie.fr/software).

Job description and skills

We expect a candidate with a background in computational systems biology. The successful candidate should be familiar with standard approaches of omics data analysis in biology and have some knowledge of mathematical modeling of cellular processes. Ideally, the candidate would be proficient in Python or R languages.

The project would involve strong collaborations with biologists, clinicians, and computational biologists. Excellent communication skills, team spirit, and a capacity to work in autonomy are essential. Fluent English, both spoken and written, is also required.

The candidate will be involved in an EU project focused on colon cancer. She/he will be in charge of gathering patient data, applying standard statistical data analyses to cluster patients, developing computational methods for improving data integration into Boolean models and applying them to personalize models to patients with the purpose to suggest optimized combinations of drugs. The models will be validated on experimental data and past clinical trials.