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Field
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, focusing on applications within the healthcare, education, and environment sectors. Designs generative AI techniques and algorithms for data integration and computational models, with objectives to amplify
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Research Fellow in Intervention Development to join the Big Data in Health Grou About us Our big data in health team at the University of Southampton is based in the Primary Care Research Centre. We
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cooperative, competitive, and mixed settings. Collaborative decision-making frameworks and decentralized learning algorithms. Adaptive, meta-learning, and context-aware strategies to enhance policy
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to remove PFAS. To accomplish these goals, the candidate will participate in the development of AI/ML algorithms for the prediction of chemical properties, infrared and mass spectra, and ionization cross
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the following tasks: Development of new large language models for process modeling Development of new decision-making algorithms Provide regular project updates to principal investigator and funding agency Report
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interaction and analytics using AI. Key Responsibilities: Development of artificial intelligence (AI) technologies to perform human-robot interaction and analytics System integration of the developed algorithms
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Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project
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project ”Decoding Death and Dying in People with Dementia by Digital thanotyping (5-D)”, financed by the European Research Council (ERC). The 5-D project will develop methods and digital tools to identify
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Information Engineering and Media to develop Machine Learning and AI algorithms for real-world and media-related applications. The Research Associate/Research Fellow is also expected to support teaching
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learning, and data science, focusing on applications within the healthcare, education, and environment sectors. Designs generative AI techniques and algorithms for data integration and computational models