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for Postdoctoral Researchers/Research Fellows in the following areas: Areas of interest: Privacy and Compliance, User Experience; Computational Data Science and Applications; High-performance, Energy-efficient
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PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo
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Hours: Full time (with possibility of less than full time upon agreement with Programme Director and funder) Contract: Fixed-term for 3 years Location: Liverpool/Remote/Overseas (Global South) Fully
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computational approaches towards a new project which seeks to better understand the causes and consequences of the correlation between multiple traits and to quantify trait variation that arises from new
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high consistency of quality, (3) use the knowledge gained to understand the opportunities and limitations of the process when extended to a wide range of wire and powder materials. The PhD studentship is
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research frontier in computer vision that combines three critical challenges: class imbalance, recognition of rare and unseen species, and dense labelling of high-resolution imagery. The candidate will
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application of computational tools for the early detection and deconstruction of chromosomal instability in cancer” For further information about the research group, including their most recent publications
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repair and maintenance of gas turbine engines. Applicants are invited to undertake a fully funded three-year PhD programme in partnership with Rolls-Royce to address key challenges in soft robotics
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Rolls-Royce University Technology Centre (UTC) in manufacturing and On-Wing Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership
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Rolls-Royce University Technology Centre (UTC) in Manufacturing and On-Wing Technology Applicants are invited to undertake a fully funded three-year PhD programme in partnership with industry