|Salary:||£38,587 to £50,296 Grade J or K|
|Hours:||Full Time, Part Time|
|Placed On:||4th October 2021|
|Closes:||31st October 2021|
We are seeking a talented postdoctoral scientist with expertise in biomedical data integration and analysis, data mining and/or causal inference. As the successful candidate you will join a vibrant interdisciplinary research environment in the MRC Integrative Epidemiology Unit (www.bris.ac.uk/ieu), working within a programme that applies data mining approaches to epidemiological research questions (www.biocompute.org.uk). The role will be focused on systematic analysis of high-dimensional population health datasets and knowledge graphs such as EpiGraphDB (www.epigraphdb.org) to identify risk factors, mechanistic pathways and potential intervention targets for human disease.
What will you be doing?
The role will be focused on systematic analysis of population health/biomedical datasets and knowledge graphs such as EpiGraphDB (www.epigraphdb.org) to identify risk factors, mechanistic pathways and potential intervention targets for human disease. You will be encouraged to co-develop new project ideas that align with the research objectives of the MRC IEU, in particular those focused on data/literature mining, causal inference, bioinformatics, evidence triangulation and knowledge graph analysis.
You should apply if
You have a strong computational and analytical background, with experience in data science, programming and the application of these skills in health, biomedical or biological research. Ideally you will be familiar with knowledge graphs or have an interest in developing skills in this area. You will also have experience of applied statistical analysis and/or machine learning and/or a good understanding of causal inference methods.
For informal enquiries please contact Professor Tom Gaunt: 0117 3310132 / email@example.com
Contract type: Open ended with funding until 31/03/2023
You may notice that the application form you have completed looks different to previous versions. This role is part of a blinded shortlisting pilot for academic roles, where hiring managers will not see any identifying information from candidates until interview stage. We’ve had to collect some information in a more binary manner to facilitate this’
We welcome applications from all members of our community and are particularly encouraging those from diverse groups, such as members of the LGBT+ and BAME communities, to join us.
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