685 computer-security "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" positions at University of Sheffield
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Machine Learning-Guided Discovery and Experimental Validation of Novel Antimicrobials Against Pseudomonas aeruginosa (S3.5-MPS-Soukarieh) School of Mathematical and Physical Sciences PhD Research Project Competition Funded Students Worldwide Dr Fadi Soukarieh, Dr JG Hill, Dr Esther...
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High-speed astrophysics with ULTRACAM and HiPERCAM
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Robust machine learning using information theoretic approaches for damage detection in complex machines (C3.5-ELE-Esnaola) School of Electrical and Electronic Engineering PhD Research Project Competition Funded Students Worldwide Dr Inaki Esnaola, Dr Will Jacobs Application Deadline: 15 January...
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Spatially-explicit multi-model ensemble methods for marine ecosystem prediction (C3.5-MPS-Johnson) School of Mathematical and Physical Sciences PhD Research Project Competition Funded Students Worldwide Dr Jill Johnson, Prof P Blackwell Application Deadline: 15 January 2026 Details A fully...
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computational tools is a requisite. The project supervisor is keen to provide superlative research training, transferable skills and a supportive and fun environment for every PhD student. The supervisor is
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AI-based diagnostics for fleet-based condition monitoring of electric vehicle motors using machine learning frameworks (S3.5-ELE-Panagiotou) School of Electrical and Electronic Engineering PhD Research Project Competition Funded Students Worldwide Dr Panos Panagiotou, Dr George...
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BBSRC Yorkshire Bioscience DLA Programme: Paraspeckle condensates in cell health, stress and disease - what can structural studies tell us?
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AI-based diagnostics for fleet-based condition monitoring of electric vehicle motors using machine learning frameworks (S3.5-ELE-Panagiotou)
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Physics based machine learning algorithm to assess the onset of amplitude modulation in wind turbine noise (with TNEI Group)
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pathway for particulate matter damage. Source-to-Health Modelling and Integration The final phase involves integrating the experimental data. The student will use computational and statistical methods