European Molecular Biology Laboratory
Postdoctoral Fellow Location: EMBL-EBI, Hinxton near Cambridge, UK
Staff Category: Postdoctoral Fellow Contract Duration: Estimated for 3 years (until max. 1/07/2024) Grading: Year 1 Stipend (£2,829 per month after tax) Closing Date: 2 November 2021 Reference Number: EBI01855
An exciting opportunity has been created for a talented scientist to work on the development of novel computational and informatics methods to improve target selection decision-making in drug discovery. The position is funded by Open Targets, the Illuminating the Druggable Genome (IDG) project and UK SPINE. Open Targets is a public-private initiative between EMBL-EBI, GlaxoSmithKline, BMS, Sanofi and the Sanger Institute to generate and integrate evidence on the validity of biological targets for drug development. The IDG is a large-scale NIH-funded initiative to develop informatics and experimental platforms with the ultimate goal of encouraging the wider community to investigate “understudied” proteins. UK SPINE is a network of collaborators focussed on developing new therapeutics for diseases linked with ageing. Two years’ funding is being provided by Open Targets and IDG with UK SPINE providing a third year.
Based at the European Bioinformatics Institute (EMBL-EBI) but working closely with all partners the appointee will develop computational and informatics methods that exploit the data integrated in the Open Targets Informatics Platform and IDG’s Pharos platform together with other public resources as applicable. These two resources incorporate an ever-expanding wealth of data and information pertaining to the link between target and disease phenotype, target tractability, potential safety risks and other relevant factors. The overall goal of the Open Targets-IDG project is to develop methods and insights that exploit these platforms to help drive decisions on target identification and prioritisation in the wider drug discovery and bioscience community. The UK SPINE component of the project provides an excellent opportunity to apply these concepts to diseases of ageing, working within a tight network of experimental, clinical and informatics experts to identify disease hypotheses and have these translate into experimental work.
Some of the themes that we wish to explore include data integration, the use of machine learning models to enhance target selection decisions, exploring the changing influence of different evidence over time and developing target novelty metrics. We also welcome research ideas/proposals from candidates aligned to the overall project goals and intent as part of the application process. Anyone wishing to find out more about the role is welcome to contact Dr Andrew Leach directly via email. Please include the job requisition number in the email subject.
You will have a strong scientific background, excellent attention to detail, good communication skills and be able to interact not only with experts from your immediate area of expertise but also with scientists from other areas (including, for example, colleagues who are primarily experimentalists). We anticipate that the outputs from this project will be applied to “real life” case studies within UK SPINE network but will also be incorporated into the Open Targets and IDG informatics platforms and so be available to the large number of both academic and industrial users of these systems.
A PhD (or equivalent) in a biological, chemical biology or biomedical science.
Sound knowledge of disease biology and the mechanisms of drug action.
Demonstrable hands-on expertise in at least one programming/scripting language (e.g. Python).
Practical knowledge of modern machine learning techniques
Experience in data handling, file manipulation
Good understanding of statistical methods and their application to data analysis
Ability to work accurately and quickly to meet deadlines
Ability to work independently and as part of a team
Good communication skills (both verbal and presentational)You might also have
Practical experience working in a drug discovery and development environment.
Some knowledge of the diseases associated with ageing