UMC Groningen – PhD student biomedical data science, ontologies and linked data

Job description

We are looking for a PhD student for our ‘FAIR’ research line towards integrated analysis of large biobanks and multi-center studies in (rare)disease. Big data holds huge promise to accelerate research in human health and disease, but biomedical data is very heterogeneous and fragmented impeding integrated analysis. You will research ontologies and linked data models and methods and develop smart data integration tools for large scale retrospective data integration and ‘federated’ analysis, considering the fact that health data is often privacy sensitive and involve security/anonymity constraints. You will publish 3+ publications and present at international conferences together with your PI and colleagues. Your laboratory will be our participation in large (inter)national research projects (e.g. EUCAN-Connect, LifeCycle, BBMRI, ELIXIR, Solve-RD, CORBEL) and the MOLGENIS open source software (Java/Python/Javascript/Html/REST/R) where you can impact users that use your clever models, methods and tools on a daily basis to further science and improve health care.

Work environment

We offer an exciting multidisciplinary environment with many international collaborations in the area of area of biobanking, cohorts, (rare) disease, multi-omics and data science/bioinformatics. The position is part of the Genomics Coordination Centre (GCC), the ‘big data’ research & service hub of the Department of Genetics, University Medical Centre Groningen (UMCG) and University of Groningen (rank 66 worldwide, 3rd best place to work in EU). Our mission is to accelerate scientific discovery in health data with innovative methods and tools that expedite medical research and improves people’s lives.

GCC is at the heart of the exciting big data transformation in life sciences with large population biobanks and patient cohorts and new biotechnologies producing terabytes of epidemiological genetic, molecular and imaging data offering unprecedented possibilities to diagnose disease and improve health status. You will be part of a social and ambitious team of 1 professor, 2 postdocs, 4 project/team leaders, 1 community manager, 8 programmers (2 scrum teams), 4 data managers and 4 Phd students, all on a mission to enable large scale integrated health data analyses towards better understanding and prediction of disease and health.

What do we need

The ideal candidate has a MSc in Data Science, Artificial Intelligence, Bioinformatics, Computer Science or a related field who:

  • Has a passion for data models/ontologies/linked data/semantic methods/knowledge engineering
  • Loves to translate theory into software that can be widely used in practice
  • Thrives in international collaborations and with researchers from other disciplines
  • Has pro-active, can do, collaborative, open attitude
  • Communicates easily in English speech and scientific writing (with good publication track record)
  • Is prepared to travel (inter)nationally

Read more!