35 computer-science-programming-languages-"U.S"-"U.S" PhD positions at University of Nottingham in United Kingdom
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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging
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research programme funded by the Academy of Medical Sciences Springboard award. This project aims to explore the role of these neighbouring glycoproteins in neurotrophin-mediated neuronal development as
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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 Applicants are invited to undertake a fully funded three-year PhD programme in partnership with industry
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are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The successful candidate will be based at the Rolls-Royce
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candidates with: • Relevant subject matter experience at required level (e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) • Willingness to adapt and work across different
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(School of Computer Science) External Partner: Build Test Solutions Ltd (BTS) Start Date: 1st October 2025 Eligibility: Home students only | Minimum 2:1 in a relevant discipline Stipend: Home students only
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computer literacy, good inter-personal communications skills. Desirable skills: A Master in Health Economics with experience in cost effective analyses. Funding notes The three year studentship covers UK
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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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PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience