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Field
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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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algorithm that reliably simulates two-phase flow. The PhD projects will be part of developing and analyzing relevant numerical methods and implement them in an open-source framework that will be made openly
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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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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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of the art in emerging wireless networks; - identify and select the methodologies and approaches most suitable for the development of the work; - strengthen the research and development competencies
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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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; - collaborate in the preparation of technical reports on the algorithms, mechanisms, models, or protocols developed; - develop new modules to enable the simulation and/or experimentation of emerging wireless
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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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. There are opportunities to broaden out into other areas such as new algorithm development, and advanced computational methodologies for integrated analyses. You will have a key role in planning, designing and executing a
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of a multi-modal dataset.; - Implementation of a software module for storing datasets according to a pre-defined standard.; - Development of routines for testing existing ML algorithms on a multimodal