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Funder: EPSRC and Rolls-Royce Duration: 3.5 years from 1 October 2026 Supervisors: Prof Howard Stone Location: The PhD studentship will be based at the University of Cambridge in the Department
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PhD Studentship in Aeronautics: How offshore wind farms and clouds interact: Maximising performance with scientific machine learning (AE0078) Start: Between 1 August 2026 and 1 July 2027
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Resources: Benefit from state-of-the-art High-Performance Computing (HPC) facilities, unique multimodal datasets, and advanced wearable technologies. Global Collaboration: Extensive technical and
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for medical time-series. Cutting-Edge Resources: Benefit from state-of-the-art High-Performance Computing (HPC) facilities, unique multimodal datasets, and advanced wearable technologies. Global Collaboration
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under the supervision of Prof. Emilio Martinez-Paneda on developing advanced computational tools to predict the nucleation and growth of cracks. The student will have access to state-of-the-art high
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conducted on qualified candidates for the position. The Department of Chemistry performs research, educational activities, and innovation at a high international level within e.g. energy, catalysis, and
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2026 - 12:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within
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Civil Engineering PhD Research Project Directly Funded UK Students Prof R Dwyer-Joyce Application Deadline: 30 December 2025 Details Novel Sealing for High-Pressure H2 and Low-Carbon Storage Technologies
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Starting Date 1 Apr 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer
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. Computational tools for simulating such processes - both traditional based e.g. on computational fluid dynamics and more recent based on AI/machine learning - constitute fundamental scientific domains that act as