This Master's program, part of the Interdisciplinary Approaches to Data Science (AISD) initiative, focuses on applying data science techniques to biotechnology. It aims to equip students with the skills to analyze large datasets within the biotech field, leveraging the most recent tools for information extraction. The program emphasizes an interdisciplinary approach, bringing together students from diverse backgrounds like biology, medicine, and computer science to collaborate on data-driven projects.
The curriculum is divided into two years (M1 and M2), with the M2 year detailed below. It includes both theoretical coursework and practical project work, culminating in a Master's internship.
Graduates are prepared for doctoral studies in public or private research laboratories, or for further specialization in management roles within the biotechnology sector.
Selection for M1 and M2 is based on a review of your application file, including your previous studies, grades in relevant subjects, motivation letter, and professional project. A pre-selection is followed by a mandatory oral interview.
Tuition fees are subject to change and can be found on the university's official website.