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Project title: Privacy/Security Risks in Machine/Federated Learning systems Supervisory Team: Dr Han Wu Project description: In the wake of growing data privacy concerns and the enactment
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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
of next generation agentic AI systems. In this PhD programme, you will redefine how the world works, learns, and discovers, turning bold ideas into tools used by millions. You will then become one
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qualification/experience in statistics, bioinformatics, computer science, computational biology, genomics, or a related discipline. They will have experience applying statistics and/or machine learning
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researcher to help us deliver it. By combining coherent Raman scattering with machine-learning models trained on plant mutants, the project will shed new light on the cellular-level biochemistry that governs
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applications to external bodies. We’re looking for a highly motivated scientist with: A PhD in Physics, Chemistry, or Biochemistry. Proven expertise in Raman/IR spectroscopy & machine learning classification
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a much stronger focus on experiential learning. This includes significant amounts of small group task-based working and research projects as part of the curriculum. About you You will: Possess
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-quality research outputs. You will be to support the design, delivery and production of teaching and learning material for a range of core postgraduate modules within our MA Education programmes. You will