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Field
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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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or computational frameworks. Strong interest in method development, including algorithms and/or scientific software development, with a willingness to contribute to codebases or tool creation. Evidence of
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing
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and confidence as they digitalize. For more details, please view https://www.ntu.edu.sg/dtc Job Requirements: Conduct advanced research in Generative AI, focusing on the design, development, and
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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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-leading database of MRI images of childhood tumours and have developed AI approaches to diagnose different types of tumour. To be useful for patients, this needs to be delivered in hospitals in real time
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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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barriers and enablers for cVPP adoption across diverse BC communities (including low-income, vulnerable, and Indigenous groups); (2) develop a technically feasible BC Hydro–to–cVPP coordination framework
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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