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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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this, the postdoctoral researcher will combine machine learning, molecular dynamics simulations and high performance computing (Isambard AI). Applicants must have a PhD in an appropriate area of computational chemistry or
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therefore work in a highly interdisciplinary environment spanning machine learning, speech and audio processing, computer vision, respiratory physiology and clinical medicine. You should have a PhD, or
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the School of Computer Science at the University of Sheffield, you will lead the machine learning research on acoustic foundation models for respiratory health. You will work with large-scale real-world
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predictions of river flow direction and connectivity. You will lead the development of scalable and reproducible data and machine-learning pipelines, upgrade the GRIT global hydrography, and design and evaluate
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Are you a computer scientist or machine-learning researcher interested in making medical-imaging AI work reliably beyond the dataset on which it was developed? We have an exciting two-year Grade 7
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near completion of) in Machine Learning or Maths. Informal enquiries may be addressed to [email protected] For more information about working at the Department, see www.eng.ox.ac.uk/about/work
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and machine learning methodology to help deal with key challenges in developing such models in large-scale observational electronic healthcare record data. These models will be applied to important real
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outcome sets. You will either need a PhD (or be nearing completion), in computer science, data science, artificial intelligence/machine learning (AI/ML), health data science, bioinformatics or a related
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, with opportunities to lead analyses, develop new expertise and contribute to high-impact scientific publications, and must have: A PhD, or equivalent research experience, in computer sciences