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Are you interested in developing interpretable AI models for the next generation of green syntheses? Do you have experience in AI/Machine Learning, or computational modelling of organic reactions
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deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The researcher will conduct internationally-leading research in human factors with applications
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, you will apply machine learning (ML) methods to discover reduced-order models from data and develop GenAI-based techniques for generating high-resolution climate projections. In addition to developing
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and the associated vulnerability patterns in aging and neuropsychiatric disorders using multimodal neuroimaging and machine learning methods. We are interested in the large-scale brain structural and
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and energy materials. Preference will be given to those with knowledge of computer programming, AI and/or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766
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Full-time: 35 hours per week Fixed term: 6 months Develop machine learning of cellular automata models with applications to in vitro developmental biology. The Opportunity: This post is full-time
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, machine learning and AI-based computational tools to advance biomedical as well as oncology research. The fellow will work under the supervision of Dr. Veera Baladandayuthapani and there will be
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computational statistics, statistical machine learning, simulation and statistical programming). The postholders will join the dynamic and collaborative Department of Statistics. The Department carries out world
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or machine learning applied to membrane materials or separation performance analysis is a strong advantage. • Candidates with strong experimental backgrounds, or combined experimental–computational expertise
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machine learning models and neural circuits in the brain process states of emotion. The Nair group combines cutting-edge systems neuroscience tools with the development of new AI methods to understand and