Galapagos NV
Galapagos BV - Multi-scale model for lung fibrosis

Study phase

WO Pre-Master, WO Master, WO Afgestudeerd





Required languages



Analist, Engineering, Medisch, Research & development, Wetenschap


Chemie, Engineering, Farmaceutisch



Place of work

Deels op kantoor

About us

Galapagos (Euronext & NASDAQ: GLPG) is a fully integrated biotechnology company specialized in the discovery and development of small molecule medicines with novel modes of action. Our pipeline comprises Phase 3, 2, 1, pre-clinical and discovery studies in inflammation, fibrosis, osteoarthritis and other indications. We have discovered and developed filgotinib, a JAK1-selective inhibitor for inflammatory indications now available to patients in Europe and Japan under the brand name Jyselica. Galapagos is focused on the development and commercialization of novel medicines that will improve people’s lives. The Galapagos group, has over 1000 employees, operating from its Mechelen, Belgium headquarters and facilities in The Netherlands, France, Switzerland and the US. 

Job description

The overarching aim of the internship is to develop mechanistic insights, with mathemetical models, on understanding of disease pathways playing a causal role in the development of IPF (idiopathic pulmonary fibrosis). With these models as a starting point, the intern will develop and modify these, to incorporate the pharmacology of candidate drugs, under investigation in Galapagos. The anticipated output is a multi-scale model validated with observed data from at least 2 clinical candidates.


  • The Candidate must be a currently enrolled in an MSc degree program in Bioinformatics, Biomedical Sciences, Mathematics/Statistics, or related areas.
  • Familiarity with quantitative methods and/or modelling in one-two domains among the following: mathematical, statistical, biological, pharmacological.
  • Good English oral and written communication skills
  • Must be available to work full-time (100%) for 9 months  beginning in Q2 of 2022.
  • Computational skills and interest in programming in languages such as, MATLAB, R or Python
  • Preferred:   Familiarity with systems pharmacology modelling, specifically ODEs and PDEs.

Working conditions