333 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" PhD scholarships in United Kingdom
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will be based at the University of Birmingham and supervised by Professor Russell Beale and Dr Renate Reniers, who bring expertise in the areas of human computer interaction and psychology respectively
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an allied field. An MSc degree in a relevant area is desirable though not necessary. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning
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Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 36-month PhD studentship will contribute to cutting-edge advancements in automated drug discovery through
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. Funding: Full coverage of tuition fees and an annual tax-free stipend of £22,780 for Home, EU and International students. Find out more about fee status at: https://www.imperial.ac.uk/study/pg/fees-and
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status at: https://www.imperial.ac.uk/study/pg/fees-and-funding/tuition-fees/fee-status/ . Eligibility: Due to the competitive nature of our studentships, candidates will be expected to achieve/have
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, robotics, and machine learning. You will work within a multidisciplinary supervisory team spanning engineering, robotics, and computer science, and collaborate with researchers working on real-world
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structures, access to space, multidisciplinary design and concurrent engineering, uncertainty treatment and optimisation, machine learning. (https://www.strath.ac.uk/ ) Task description for your Individual
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characterisation and radionuclide partitioning using specialised experimental facilities within the NNUF RADER facility (https://www.nnuf.ac.uk/rader ). This will include the use of state-of-the-art facilities
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candidates with an exceptional track record may also be considered. For further information and guidance, please contact Dr Mingee Chung at m.chung@bham.ac.uk References: https://www.birmingham.ac.uk/news/2024
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tailored trajectory guidance. Enhancing Robot Autonomy: Enabling robots to improve their own performance by learning from operator data, ultimately enhancing their ability to assist in complex tasks. Key