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of Educational Gains, Skills, Apprenticeships and Foundation Programmes. Foster impactful civic and global relationships to support ESE initiatives and funding opportunities. Build and maintain effective strategic
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Open PhD position: Autonomous Bioactivity Searching Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 42-month funded PhD studentship will contribute to cutting-edge advancements in automated drug discovery through the integration of high data-density...
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. You will manage, plan and conduct research with Dr Sollini’s leadership, resolve problems that arise, write up your research findings and work closely with other people within the lab. There is also the
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of Veterinary Medicine and Science on Sutton Bonington Campus. The selected individual will provide critical administrative assistance for Postgraduate Research (PGR) and Postgraduate Taught (PGT) programmes
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PhD Studentship: Revolutionising Litz Wire Development for Next Generation Ultra-High Speed Propulsion Motors The Manufacturing Technology Centre UK, and University of Nottingham This project offers an exciting opportunity to undertake industrially linked research with leading engineers at the...
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some of the very best students from around the world to its excellent undergraduate, Masters and PhD programmes. All of our academics also contribute to School administration. We believe that every one
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the results of this project. Candidates must possess a good first Degree (or Master's) and PhD (or near competition) in Engineering, Mathematics, Physics, Computer Science, or related disciplines. Your working
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position at the level of assistantprofessor. The School of Mathematical Sciences currently runs two degree programmes, which lead successful graduates to University of Nottingham degrees in BSc Honours
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project which aims to understand which computational (reinforcement learning) mechanisms are engaged by different antidepressant treatments and through this improve targeting of future treatments for
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to understand which computational (reinforcement learning) mechanisms are engaged by different antidepressant treatments and through this improve targeting of future treatments for clinical depression