428 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" Fellowship positions in United Kingdom
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& Professional Learning team. -All FMH staff are entitled to ten days staff development per year (pro rata). Please speak to your Line Manager about how you can utilise these. Access to on-site childcare, shopping
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programming such as Python, R, MATLAB, or other similar programs and experience in using simulation/optimisation models and advanced data handling techniques e.g. machine-learning techniques, statistics
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) at Liverpool John Moores University, UK. LOOM enjoys an international research reputation on maritime risk studies, https://www.ljmu.ac.uk/research/centres-and-institutes/loom . In return, we offer an excellent
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(W.L.King@soton.ac.uk ). Working at the University of Southampton: Check out the staff benefits and why you should join us at The University of Southampton. Where to apply Website https
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to the patient. Further information can be found on our website http://www.ucl.ac.uk/pharmacy/ About the role This is an exciting opportunity to join the Research Department of Practice and Policy, conducting
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Date: 19 Jan 2026 Category: Research and Teaching (R&T) Where to apply Website https://academicpositions.com/ad/university-of-nottingham/2026/rights-lab-resea… Requirements Research FieldJuridical
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. We support staff wellbeing with flexible working options, work-life balance initiatives and support for physical and mental health. You can find more detail on all of this and more at https
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establishing a strong academic track record. You may have worked in MRI research previously or have strong computational / AI / machine learning skills used in other areas of research. Essential criteria PhD
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for MND which could be translated into the clinic. The idea is to use cutting edge machine learning to create clinically actionable predictions such as the time from diagnosis to requirement for a
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2028 working 21 hours per week. We are looking for a Senior Research Fellow in Statistics to advance the dynamic research portfolio of the Population Data Science group (https://popdatasci.swan.ac.uk