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Field
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will pioneer mathematical frameworks for multimodal integration, advance video transformer architectures for temporal-spatial dynamics, and develop few-shot learning methodologies for ultra-low-resource
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living. Empa is a research institution of the ETH Domain. Per- and polyfluoroalkyl substances (PFASs) are a...
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, Flemisch 2020. DuMuˣ 3 - an open-source simulator for solving flow and transport problems in porous media with a focus on model coupling. Computers & Mathematics with Applications. https://doi.org/10.1016
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contribution to addressing the major societal challenges of the future. The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics
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systems thinking mindset with robust mathematical frameworks to solve real world problems with our industrial collaborators at Rolls-Royce. Over the past 30 years, we have designed and introduced new
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. The successful applicant will join the Biomedical Signals and Systems (BSS) group of the department of Electrical Engineering at the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS). As
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contribution to addressing the major societal challenges of the future. The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics
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dedicated PhD student with a 1st class or 2:1 degree in the field of Engineering, Mathematics, Physics, Architecture or Computer Science. A MSc degree in a relevant area is desirable though not necessary
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, Regional Science, Economic/Quantitative Geography, or Mathematics knowledge and experience in spatial equilibrium modeling (e.g., through coursework, thesis work, or previous projects) is beneficial
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related field. Strong affinity (e.g. via advanced courses or projects) with first-principles mathematical modelling of thermal systems, model reduction, system identification, machine learning. Programming