|Salary:||£2,752.13 monthly starting stipend after tax (Year 1 Stipend).|
|Placed On:||10th June 2019|
|Closes:||19th July 2019|
About the team/job
This is an exciting opportunity to work at the cutting edge of evidence generation in fast moving field of drug target identification and prioritisation. You will be embedded in a team working with cloud based technologies, integrating evidence from across EMBL-EBI and other databases to identify and prioritise drug targets.
The scientific literature is a rich source of evidence for the role of potential drug targets in disease, as well as other relationships between targets, disease, drugs, methods and so on. We are developing a robust pipeline to extract these relationships from the Open Access literature working with Europe PMC and developing machine learning and graph approaches for identifying novel and unexpected relationships.
The post will involve use of natural language processing to develop comprehensive entity recognition, testing and refinement of entity dictionaries, building a knowledge graph combining literature relationships with other evidence from the Open Targets Platform and machine learning to predict novel relationships including disease:target associations and drug repurposing opportunities.
You might also have
The position is embedded in the Open Targets Core Platform team. Extensive interaction with text mining and NLP experts in Europe PMC is required. Interaction with the full set of Open Targets Partners is expected.
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