560 parallel-computing-numerical-methods-"Simons-Foundation" Postdoctoral positions in United Kingdom
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& Health Informatics. Contact details:Prof Vicky Slonims. Vicky.slonims@nhs.net Location: St Thomas' Campus (Becket House). Category: Research. About us: Applications are invited for a Research Assistant
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. The impact of C(E)TRs on clinical and other outcomes has not been extensively studied. The OptiCaT research programme takes a mixed methods approach. The successful applicant will have a key role in the
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research programme takes a mixed methods approach. The successful applicant will have a key role in the qualitative work package which aims to understand multi-stakeholder perspectives of the C(E)TR process
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techniques and numerical modelling. About the role A successful candidate will join the EPSRC-funded Programme Grant Next Generation Metamaterials: Exploiting Four Dimensions (META4D: www.meta4d.co.uk
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nonlinear Fourier Transform. Previous experience in the analytical investigation and numerical modelling of light propagation in nonlinear optical fibres, fibre lasers or resonators is required. Previous
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, engineering and AI with industry scientists, forming small teams focused on ambitious, ‘blue sky’ research for novel methods development relevant for drug discovery analysis pipelines, trial design and
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. The research will involve both analytical work and numerical computations. The balance between analytical and numerical type work is flexible and can depend on the preferences and skills of the successful
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-performance or cloud computing environments. Need strong data management and database skills, expertise in clinical phenotyping ontologies and the application of machine-learning/AI methods to biomedical data
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balance, offering: (i) flexible working and parental leave opportunities; (ii) an employee assistance programme which provides free, confidential advice on both home and work concerns, as well as optional
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-performance or cloud computing environments. Need strong data management and database skills, expertise in clinical phenotyping ontologies and the application of machine-learning/AI methods to biomedical data