Postdoctoral Fellow

European Molecular Biology Laboratory (EMBL)

Contract Duration: 2 years.

Job Description

We are looking for a Postdoctoral fellow to develop computational approaches to integrate gene functional and physical interactions networks with target-disease association data with a view of studying how association evidence among network members can best be combined for disease phenotype predictions, pathway stratification, and drug target identification. This post is a part of a project funded by the Open Targets initiative aiming at integrating association genetics and prior knowledge from protein/gene networks.

Our group is interested in studying genotype to phenotype associations by taking into account structural and cell biology knowledge. Within this broad scope we have, for example, been integrating different variant effect predictors in order to interpret the molecular consequences that are intermediate between genotype and phenotype. The applicant would aim to develop novel frameworks to integrate prior knowledge network information, large scale gene expression, and protein abundance data across human samples, protein structural information, gene essentiality screens, and large scale genomic association information (GWAS, eQTL, and pQLT). You can learn more about our research group here.

EMBL-EBI is part of the European Molecular Biology Laboratory (EMBL) and it is a world-leading bioinformatics centre providing biological data to the scientific community with expertise in data storage, analysis, and representation. We have close ties with both the University of Cambridge and the Wellcome Trust Sanger Institute.

Open Targets is a pioneering public-private partnership between Biogen, EMBL-EBI, GSK, and the WTSI. Open Targets aims to generate evidence on the biological validity of therapeutic targets and provide an initial assessment of the likely effectiveness of pharmacological intervention on these targets, using genome-scale experiments and analysis. Open Targets aims to provide an R&D framework that applies to all aspects of human disease, and to share its data openly with the scientific community.

Qualifications and Experience

Considered applicants must hold a PhD in Life Sciences and have previous experience in computational biology. The ideal candidate will have expertise in analysis of large-scale genomics data. Experience in functional association networks, structural bioinformatics, or drug target predictions methods are considered an asset. The post holder should enjoy working in a highly collaborative and interdisciplinary environment. Good written and oral communication skills are essential.


EMBL is an inclusive, equal opportunity employer offering attractive conditions and benefits appropriate to an international research organisation.

We have an informal culture, international working environment and excellent professional development opportunities, but one of the really amazing things about us is the concentration of technical and scientific expertise – something you probably won’t find anywhere else.

If you’ve ever visited the campus you’ll have experienced first-hand our friendly, collegial, and supportive atmosphere, set in the beautiful Cambridgeshire countryside. Our staff also enjoy excellent sports facilities including a gym, a free shuttle bus, an on-site nursery, cafés and restaurant, and a library.

Application Instructions

To apply please submit a covering letter and CV, with two referees, through our online system.

Informal enquiries about the post can be directed to

Additional Information

Applications are welcome from all nationalities. EMBL-EBI is committed to achieving gender balance and strongly encourages applications from women.

Applications will close at 23:00 GMT on the date listed above.

Share this job
  Share by Email   Print this job   More sharing options
We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
Advert information

Type / Role: