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, machine learning, energy technology or related subjects Prior experience in building predictive models using regression techniques, neural networks (CNN, GNN) or symbolic regression Experience in
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including antenna and/or microwave engineering * programming skills and working knowledge of Matlab programming environment * knowledge of mathematical modelling, machine learning and artificial intelligence
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optimal transport and gradient flows to machine learning and optimization applications, such as deep generative models, sampling, inference, stochastic optimization, and beyond. The doctoral student will
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that challenge prevailing assumptions, employ cutting-edge technologies, or integrate machine learning with neurobiological data are especially welcomed. Projects focusing primarily on animal models with
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research in hydrogeophysics, including areas such as field-based geophysical observations, computational modeling, and AI-driven analysis. Essential FunctionsEmpty heading Teach undergraduate and graduate
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to optimise built-environment thermodynamics and occupant comfort by creating predictive AI tools for spatiotemporal heat transfer. Machine learning algorithms will identify energy inefficiencies and propose
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promise and peril of hybrid intelligence—humans and machines working and learning together. Our mission is to establish an internationally leading interdisciplinary hub that advances foundational research
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students, our community, and our country can become. Visit www.LaGuardia.edu to learn more. Connections working at CUNY La Guardia Community College More Jobs from This Employer https://main.hercjobs.org
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in neuroimaging, applied data science and/or machine learning are desirable. Funding & how to apply The scholarship will fund course fees up to the value of home fees*, a tax-free stipend in line with
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mathematical modeling and programming. * Research experience and publications in machine learning, complex networks, and mathematical modeling. * Excellent English communication skills (written and oral