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About the project: Machine learning accelerated Inverse Design of Graphene Nanoribbons for Green Energy Supervisor: Dr Sara Sangtarash, University of Warwick Thermoelectric materials convert heat
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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PhD Studentship: Robust, Certified, and Scalable Federated Machine Unlearning for Privacy-Preserving AI About the Project As federated learning systems become increasingly embedded in high‑stakes
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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
We welcome applications from candidates with a broad range of academic backgrounds and experiences for a 4-year PhD project on Mathematical and Machine Learning Aspects in Crystallography at Durham
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and advanced machine learning. The project will integrate measurements from the SWOT satellite mission with Oxford's Global River Topology (GRIT) hydrography to develop verified, uncertainty-aware
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, classics, gender studies, political science, and international studies—with cutting-edge data science techniques, including Earth Observation (EO) data analysis, machine learning, large-scale collation and
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integrating power electronic converters and electrical machines we can use common structures and systems to greatly reduce, material usage and energy consumption. Through a multidisciplinary research approach
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integrating power electronic converters and electrical machines we can use common structures and systems to greatly reduce, material usage and energy consumption. Through a multidisciplinary research approach
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will be responsible for the follow : (full details of duties available from the Job Description) Research Collaboration and engagement You will have completed a PhD in machine learning, computer science
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AI and data science, particularly in dynamic settings where observations are collected sequentially and decisions influence future outcomes. This project will develop novel machine learning and