About

Doctoral program Quantitative Biology

The advent of large-throughput data is transforming life sciences into an increasingly quantitative discipline. UNIL FBM is at the forefront of this revolution, with about 15 research groups primarily active in computational biology, and many other groups with some computational biology research component. This is also reflected in the recent inception of the Department of Computational Biology. UNIL hosts the headquarters of the Swiss Institute of Bioinformatics, to which many groups are also affiliated.

 

The aims of the doctoral program in Quantitative Biology are to 1) attract top students who want to pursue a career in computational biology research or deepen their quantitative biology skills and to 2) provide them with first-rate training.

 

We foresee three main types of incoming students and associated objectives:

  1. Students with a life science degree, embedded in experimental lab: high degree of motivation to learn fundamentals of computational biology, and to develop skills to use computational tools more effectively
  2. Students with a life science degree, embedded in computational lab: deepen their quantitative skills and broaden their horizon in terms of experimental and computational techniques.
  3. Students with non-biological background (CS, math, physics): high degree of motivation to work in life science. New tutorial in first year to catch up with biological fundamentals.

 

Recognizing that tight collaboration between computational and experimental biologists is key, the program puts a special emphasis on harnessing and developing computational approaches to answer questions that are relevant to biological and medical research. As such, we expect the program to be of interest both to students developing new computational methods in their doctoral work, and students wanting to use and interpret state-of-the-art computational methods in their doctoral work. Thus, we expect interest in the program by students from all across the UNIL Faculty of Biology and Medicine.