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type (iv) work with the computational biology team to transfer this information into a AI algorithm that can distinguish neurodegenerative and neuroprotective phenotypes (v) work with colleagues in
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for AI based algorithms. Research experience in these areas will be highly valued. The successful candidate will also contribute to the formulation and submission of research publications, development
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in implementing, testing and validating complex minimisation algorithms that can be used for adaptive trials. Application & interview 8 Experience of collaborating on successful research proposals
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expectation to contribute to scientific publications and demonstrations. Support will be provided by senior colleagues in the Digital Manufacturing Laboratory. You will have completed a First degree in Computer
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in at any time. Background The School of Mathematics welcomes applications for a research fellowship in statistics to work on the UKRI Future Leaders Fellowship project ‘Computational Statistics
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dynamics, solid mechanics, soft matter or active matter. • To become familiar with simulation algorithms as needed, assist in the development of new ones, test and document any newly developed
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Bay. The key responsibilities of this role include; Using a combination of automated algorithms and manual data processing to identify bottlenose dolphin signature whistles in a multi-year acoustic
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algorithms, and decision-support tool development. Responsibilities will include programming, analysing and interpreting data, and contributing to innovative solutions that support maritime decarbonisation
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development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning algorithms might support the wider integration of, and uptake
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Programme: Hybrid CFD and process simulation for process intensification of post-combustion CO2 capture School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof