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Field
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Research Fellow in Intervention Development to join the Big Data in Health Group About us Our big data in health team at the University of Southampton is based in the Primary Care Research Centre
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motivated the development of Federated Learning (FL) [1,2], a framework for on-device collaborative training of machine learning models. FL algorithms like FedAvg [3] allow clients to train a common global
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the UK Space Agency, European Space Agency (ESA), NASA and Teledyne e2v. A main focus for the CEI is the development and characterisation of detectors for space missions. One such mission is the Habitable
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. The researcher will utilize machine learning and AI techniques to analyze data and contribute to the development of predictive models. This position offers a unique opportunity to gain hands-on experience in
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Automation group will develop novel machine-learning based control algorithms that allow for real-time adjustment of OSA therapy. The main challenge is to develop robust machine learning algorithm which can
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of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. We are seeking a Research Associate to join MMLab@NTU. Successful candidates will conduct research and develop
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all project deliverables are met. Undertake these responsibilities in the project: Conduct technology review of sensor technology Develop algorithms/models for engine health monitoring Develop prototype
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expertise by developing an e-commerce website prototype with the developed algorithm embedded within the prototype, ensuring its full functionality and integration. Reports to: Project Lead Project name
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algorithms in extremely complex and enormously large spaces motivated by physics and chemistry Developing interpretable AI for scientific discovery in physics (example here ) Formal mathematics (using Lean’s
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. The monitoring of telecommunications and energy production and distribution networks are characteristic examples of such time-critical applications. The project aims to propose unsupervised online CPD algorithms