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Open PhD position: Autonomous Bioactivity Searching Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 42-month funded PhD studentship will contribute to cutting
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supervisors spans five departments at University of Nottingham including Architecture and Built Environment, Electrical and Electronic Engineering, Mathematics, Physics and Social Sciences. The PhD programme
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Applications are sought for a fully-funded 42 month PhD studentship to work with Dr Rachel Nicks and Prof Stephen Coombes on the project: White Matter Computation: Utilising axonal delays to sculpt
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BRC PhD: Improving recovery from pneumonia after hospitalisation Applications are invited from UK students for a three-year PhD studentship funded by the NIHR Nottingham Biomedical Research Centre
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Discover your career The world of the University of Nottingham is defined by our people and the values we share. Our environment is an ambitious vision brought to life across vibrant and forward-thinking global campuses. An ever changing world where open minds and diverse cultures are able to...
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The Faculty of Science AI Doctoral Training Centre (DTC) invites applications from Home students for fully-funded PhD studentships to carry out multidisciplinary research in the world-transforming
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aligned with your PhD research proposal, in the programme of Architecture Design (Social Science). Deadline: 11.59 pm on the 16th of February 2025. Late proposals for this funding will not be considered
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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms Background Network Rail operates several telecom networks which provide connectivity for various...
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EPSRC Centre for Doctoral Training (CDT) PhD in Digital Metal with BAE Systems (Enhanced Stipend) Solid-state Additive Manufacturing of Nickel Aluminium Bronze alloys Background UK Applicants
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Fully-funded PhD Studentship: Adaptive Mesh Refinement for More Efficient Predictions of Wall Boiling Bubble Dynamics This exciting opportunity is based within the Fluids and Thermal Engineering