847 phd-computer-science-"IMPRS-ML"-"IMPRS-ML" Fellowship positions in United Kingdom
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collaboration with Dr Elizabeth Duncan (Leeds) and Prof Rhonda Snook (Stockholm). You will join our network on Thermal Fertility Limits funded by the European Society for Evolutionary Biology. This knowledge will
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trustworthy, conscientious, innovative experimental scientist who has successfully completed a PhD in Materials Science, Chemistry, Bioengineering (or similar), Polymer Science or have equivalent experience
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expertise ranging from mathematical modelling to chemistry, molecular and cell biology, material sciences and engineering, and medical devices. The Research Fellow will be working in collaboration with
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Job id: 125445. Salary: £38,831 - £73,992 per annum, plus £2,152 London Weighting Allowance. Posted: 16 September 2025. Closing date: 28 September 2025. Business unit: Faculty of Life Sciences
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genome and metagenomic sequence data. The essential education and experience requirements for the post are as follows: Have or be about to obtain* a PhD in Microbiology, Pharmacy, Bioinformatics or related
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models, techniques and methods. Person Specification A first degree in Chemistry, Physics, Chemical Engineering, Materials Science or related subject, and a PhD (or close to completion) in an area relevant
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clearly demonstrate that you meet the following essential criteria: Have or about to obtain* a PhD in health economics or a cognate discipline (*must be obtained within 3 months of commencement of
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Faculty or Department: Faculty of Engineering and Applied Sciences Based at: Cranfield Campus, Cranfield, Bedfordshire Hours of work: 37 hours per week, normally worked Monday to Friday. Flexible
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this post) a PhD in molecular biology, cell biology, pharmacology or a related area of biomedicine. Previous track record of high-quality research in the field radiation biology research or cardiovascular
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Fixed Term Contract for 24 months We welcome applications from passionate and skilled post-PhD or experienced researchers in malacology, epidemiology, schistosomiasis modelling, or spatial data