36 computer-science-quantum-"https:"-"https:"-"https:"-"https:"-"https:" Fellowship positions at University of Nottingham
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Electronic Engineering, Control Engineering, Computer Science or a very closely related topic: Strong understanding of power electronics principles Excellent knowledge on data-driven machine learning algorithm
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bioinformatics, computational biology, or a related field. Proficiency with Linux operating systems is essential, as is the ability to analyse and interpret large datasets and apply critical evaluation to current
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We are seeking a highly motivated and skilled Research Associate/Fellow to join an innovative translational research programme focused on childhood brain cancer. Based at the University
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/ knowledge of lung cancer/ publications or poster/ oral presentations in lung cancer research would be desirable. Applicants should also have a PhD or equivalent in computer science, mathematics, statistics
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Health, Institute of Mental Health) and collaborate closely with the HEATMAP team, including Professor Franziska Schrodt (Earth System Science), Professor Dov Stekel (Computational Biology), Dr Tanya
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across epidemiology, building science, and exposure modelling — contributing to an ambitious international programme with direct policy relevance. Be part of a project that will influence how buildings
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the successful candidate will work closely with other colleagues and industrial partners. Candidates must hold a PhD (or be near to completion) or equivalent, in engineering, applied mathematics or a related
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outcomes over time using multi-state models, accounting for association amongst processes and across time. The role will involve both theoretical and computational model development, together
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Applications are invited for a Research Associate/Fellow on an NIHR Invention for Innovation (i4i) Programme-funded project in the Breast Cancer Pathology Research Grou within the Nottingham Breast
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multipartner cluster, supporting researchers by adapting microfluidic platforms to a range of specific tissue models. The post will be based within the School of Life Sciences with periods of secondment to Prof