Master's 2 in Epidemiology, Health Data, and Biostatistics (EDSB) with a specialization in Data Analysis for the Life Sciences

The EDSB Master 2 – Data Scientist for the Life Sciences program trains data scientists capable of working with a wide range of data from biology, health, and the life sciences more broadly. It offers a broad-based education tailored to the diversity of data and contexts encountered in both research and industry: experimental, industrial, pharmacological, and omics data, as well as data from complex measurement devices.

The track places a strong emphasis on machine learning, with a progression ranging from basic learning methods to deep learning. It shares a common foundation with the Health Data Analysis track (generalized and mixed linear models, analysis of censored data), which ensures a solid grounding in biostatistics. It expands on this foundation to address issues specific to industry and the life sciences: statistics for industry, data collection planning, advanced databases, and pharmacokinetic modeling combining mixed models and machine learning. The courses utilize R and Python.

The program relies heavily on project-based learning. Case studies and projects conducted in collaboration with other programs place students in situations that closely resemble real-world professional settings: teamwork, dialogue with specialists from other disciplines, and managing an end-to-end analysis project. Research seminars round out this interdisciplinary approach.

The program offers an apprenticeship track, which allows students to gain significant professional experience starting in the second year of the master’s program. Other students complete a six-month internship in a research laboratory or at a company. This program prepares students for careers as data scientists, biostatisticians, or research engineers in academic or hospital research laboratories, the pharmaceutical industry, the agri-food sector, or the biotechnology industry, as well as for pursuing a Ph.D.