38 parallel-and-distributed-computing-phd Fellowship positions at UNIVERSITY OF SOUTHAMPTON in United Kingdom
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experience in, for example, machine learning, high-performance computing, reconfigurable hardware, cloud computing, compiler engineering, distributed systems, or DevOps are encouraged to apply, as
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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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The Role: We are seeking an outstanding computational biologist to join the BioFAIR Pathfinder project to develop computational framework for gene regulatory network (GRN) inference methods in
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. This activity will run in parallel with commercialisation activities by discussion with stakeholders for problem validation and obtaining performance requirement definitions. What We Can Offer You Committed
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successful you will have: A PhD (or equivalent professional experience) in a discipline relevant to responsible AI, including computer science, AI, data science, science and technology studies, law, public
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We are seeking a motivated Research Fellow to join a Human Frontier Science Program (HFSP)-funded project investigating the evolutionary origins and diversification of sensory receptor and ion
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development of postgraduate and PhD researchers. You will have the opportunity to contribute to a programme of research that will inform decisions about how best to reduce disparities in maternity outcomes
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organisational settings. Applicants should have a MSc degree or PhD in psychology, neuroscience, cognitive neuroscience, or a closely related discipline. Previous experience collecting and analysing EEG data is
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Applications are invited for a Research Fellow position within the School of Electronics and Computer Science at the University of Southampton. The project will involve the development
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lives. The NIHR ARC Wessex Addiction Flagship is developing a connected programme of applied research, implementation and partnership activity focused on improving the identification of, and response