Master's degree

The proposed program is an evolution of the "Statistics for Health Sciences" program in the "Mathematics" track from the previous period. The Master 1 program will now be shared with the "Epidemiology, Health Data, Biostatistics – Data Analyst for Life Sciences" program, with which there was already significant overlap during the previous period. 

Its objective remains to provide students, mainly from health and biology degree programs, with dual expertise in biostatistics. This dual expertise is particularly sought after in the job market, as shown by the employment rate figures upon completion of the program. Our students are real assets to any team, as they have the necessary background in biology/health to understand the issues at stake and the skills to analyze data appropriately. Proper analysis of biology/health data is a major challenge for research in the coming years, as data is becoming increasingly voluminous and numerous, and errors in its analysis can lead (and have already led in the past) to erroneous or non-reproducible conclusions that discredit the entire research sector. Real expertise in data analysis is therefore essential today in order to answer complex biological questions. This objective is the "DNA" of our training program and will continue to be so in the coming period.

In addition, the primary objective of changing the name of the program is to reflect the desired background of our students: the name "Mathematics" was misleading, since we only recruit students from health and biology programs in order to offer them dual expertise in biostatistics. However, these students do not naturally seek a master's degree in mathematics.  Our visibility was therefore compromised by this affiliation.

In terms of development, it meets a need for the target audience, which will consist of health students and students changing direction who have completed the Specific Health Access Program (PASS) and the Health Access License (LAS), currently being implemented as part of the PACES reform.

In addition, we have updated the course content to enable health and biology students to acquire skills that are increasingly relevant to the biostatistics job market: introduction to the Python language, reinforcement of teaching in machine learning and artificial intelligence. This change is also consistent with the change in specialization, as the health applications of these methods are becoming increasingly numerous (biomarker research, personalized medicine, etc.).