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of methods for tasks such as data harmonisation, phenotype representation, genomic analysis and patient or gene prioritisation. Working within research high-performance computing (HPC) environments
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pipelines in R, Python and HPC or cloud environments. Collaborate with developmental biologists to interpret genomic findings, validate results and address key evolutionary questions. Support and mentor PhD
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team and supported by cutting-edge HPC and GPU infrastructure, you will contribute to internationally leading research, publish in high-impact journals and present your work at major scientific
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, exomes). Demonstrated experience as an expert level user of HPC infrastructure / Linux systems. Demonstrated experience implementing key R and / or Python packages. Track record of publications
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evidenced by publications or submitted manuscripts in refereed journals Experience with computational protein design (desirable) Experience working with cloud/HPC environments, workflow orchestration
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environment within the School of Biological Sciences, working alongside a growing computational genomics community at Southampton. You will have access to IRIDIS HPC, with support from RSEs, and also
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”. The project involves extensive discrete element modelling of clay using YADE on the Nottingham HPC. It will expose origins of continuum parameters for the primary clay minerals in London clay by performing
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”. The project involves extensive discrete element modelling of clay using YADE on the Nottingham HPC. The project will expose origins of continuum parameters for the primary clay minerals in London clay by
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refereed journals* Experience with computational protein design (desirable) Experience working with cloud/HPC environments, workflow orchestration or reproducible computational pipelines (desirable) Minimum
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or single-cell genomics analysis. Familiarity with graph neural networks, transformers, generative AI or foundation models. Experience working with cloud/HPC environments, workflow orchestration