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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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techniques which have traditionally been employed. As artificial intelligence becomes increasingly ingrained in the society, it is crucial to ensure that the machine learning algorithms not only make correct
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Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing techniques to enable large-scale data search
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decentralised algorithms, meta-information data structures and indexing techniques to enable large-scale data search across Personal Online Datastores (pods) hosted on distributed pod servers, addressing both
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AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical imaging QUALIFICATIONS Successful applicants will have: a PhD in
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should not exceed one page Desired qualifications: Good knowledge in programming language theory, algorithms, distributed systems and logic Experience with language-based techniques for information-flow
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model checkers; proofs of safety and/or security properties; programming languages and/or type systems; concurrent and/or distributed algorithms; and related topics. The successful applicant will work in
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scientists, nuclear medicine physicians) to develop and implement innovative AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical
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particular to the development and validation of novel computational language models, algorithms, and tools for spoken language-based cognitive tests for low-resource languages, and their integration with
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literature review, algorithm design, experiment design, model training, evaluation, and benchmarking. Work with and supervise undergraduate or graduate student assistants, guiding them in data collection