58 computer-programmer-"https:"-"https:"-"UNIS"-"https:"-"https:"-"https:"-"BioData" positions at University of Nottingham
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Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The
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necessarily require formal education in geotechnics. Applicants with a background in mechanical/materials engineering or alternatively mathematics/computer science with an interest in numerical modelling
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About the role - The role-holder will work collaboratively to support this Rights Lab research project. The role holder will be expected to work collaboratively as part of an interdisciplinary team, as well as undertaking independent research on the topic of risk of human trafficking among...
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Applications are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in manufacturing engineering. The successful candidate will be based
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to plan and conduct work using approaches or methodologies and techniques appropriate to the type of research, and will be responsible for writing up work for publication. You will ideally have experience
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computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and ML. The University
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computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and ML. The University
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computational arm of a Leverhulme Trust-funded project investigating how cryogenic OrbiSIMS interacts with complex biomolecular structures. Working closely with experimentalists and international collaborators
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are invited for a fully-funded Industrial Doctoral Landscape Award, offered in partnership with Rolls-Royce, to tackle key challenges in the design of aeroengine oil systems using multiphase Computational Fluid
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Electronic Engineering, Control Engineering, Computer Science or a very closely related topic: Strong understanding of power electronics principles Excellent knowledge on data-driven machine learning algorithm