340 coding-"https:"-"Prof"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" PhD positions in United Kingdom
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: Full Time Closes: 7 January2026, 23:59 GMT Application link: https://www.essex.ac.uk/postgraduate/research/doctoral-training-partnerships/aries ARIES (Advanced Research and Innovation in
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the Centre for Doctoral Training for Resilient Flood Futures (FLOOD-CDT). Further details about FLOOD-CDT can be seen at https://flood-cdt.ac.uk . Please note, that your application will be assessed upon: (1
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. More info can be found at: https://www.sheffield.ac.uk/dcs/people/academic/jefersson-alex-dos-santos About the School & Research Group The successful candidate will join the Computer Vision group in
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cell division – key to the mechanisms underpinning abnormal proliferation events, such as those contributing to cancer https://www.themitosisbooth.com . Funding Notes The 3 year studentship covers
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) or an equivalent qualification accepted by the Home Office. Applications and closing date:Monday 9 February 2026 Applicants should submit through the Abertay University jobs page https://www.abertay.ac.uk/about
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Professor Alicia O’Cathain, Lead for qualitative research in the project Direct reports Professor Alicia O’Cathain, Lead for qualitative research in the project Our website https://sheffield.ac.uk/scharr
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industrial partners, such as WAAM3D (https://waam3d.com/ ) and members of WAAMMat (https://waammat.com/ ), gaining valuable industry experience and exposure. The student is expected to acquire the following
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research community at WAMC, fostering collaboration and innovation. Additionally, there will be opportunities to work with WAMC’s industrial partners, such as WAAM3D (https://waam3d.com/ ) and members
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of Nottingham. The Rolls-Royce UTC at the University of Nottingham is a leading research institution specializing in the development of soft and continuum robots for challenging environments (https
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under uncertainty (Studentship code MSP106) Learning to sample: Meta-optimisation of gradient flows using reinforcement learning (Studentship code MSP107) Dynamic Bayesian modelling of endurance sports