26 algorithm-phd-"Prof"-"Prof" PhD positions at University of Cambridge in United Kingdom
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Applications are invited for a fully-funded 3-year PhD studentship based in the Department of Clinical Neurosciences at the University of Cambridge under the supervision of Dr Topun Austin starting
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PhD student will be trained by a team consisting of a project-specific PDRA as well as Prof. Ringe and Dr Lomonosov (senior research associate in the group), towards gaining technical independence in
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modern Bayesian modelling frameworks such as Stan, Turing.jl, and PyMC, including automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special attention will be
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our software development team, developing novel scientific algorithms and applications in the areas of spectroscopic analysis and mining of the science data catalogues extracted from the pipelines
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PhD in Civil Engineering or a relevant related field, or have equivalent industrial experience. Chartership with a Professional Engineering Institution (CEng or equivalent) is desirable. Appointment
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bioprocessing technologies to deliver efficient pathways for upcycling captured carbon into high value products. The successful candidate will have a PhD, or be studying towards a PhD, in synthetic biology or a
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A PhD is desirable but not required. Other industry, city government or research experience that demonstrates the capability to produce independent original research is also desirable. Very good
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suited to candidates with strong quantitative and analytical skills and a PhD (or near completion) in cancer epidemiology or a related field. Applicants should have experience in applying or developing
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must either have a PhD in a relevant biological subject or have submitted or about to submit their PhD thesis. Candidates must also have demonstrable expertise in biochemistry, cell biology and/or
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and experience required to perform the role are an aerothermal PhD with a combination of experimental, numerical and low order modelling experience. The PhD must be completed or near completion, and