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Job Description The section for Computational Atomic-scale Materials Design (CAMD) at the Technical University of Denmark (DTU), is seeking an outstanding and highly motivated candidate for a PhD
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exchangingexperiences with localactors (primarilyhousing organisations and municipalities). Teachingwillprimarilybe in the bachelor’s programme in Urban, Energy and Environmental Planning as well as the master’s
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affiliated with the Novo Nordisk Foundation CO₂ Research Center (CORC) , where the successful candidate will manage and coordinate projects within the CO2-to-protein program, which is a part of the CO2
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activities in CMOS circuit design, neuromorphic computing, cryogenic electronics, and spintronic-based computing systems. The role also contributes to Denmark’s and Europe’s strategic ambitions under the EU
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citizens visit to have guided tours. The veterinary programme provides research-based education, and most of the research and teaching in ruminant herd health is carried out in commercial cattle herds and
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. This program focuses on management of technology and value-creating digital transformation as well as the relationships between digital technologies, creativity, and knowledge creation. Emerging Technologies
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include research, teaching and supervision. Focusing on probabilistic modelling of existing structures, the successful candidate will carry out research related to the new research programme called Civil
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Research Mission Leader and Associate Professor in Biosolutions for Agroindustrial Biotechnology,...
affiliated with the Novo Nordisk Foundation CO2 Research Center (CORC), where the successful candidate will manage and coordinate projects within the CO2-to-protein program, which is a part of the CO2
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Position in XAI with Commonsense Knowledge for Robotics and Computer Vision 2. PhD Position in Sustainable AI for Enhancing Health Informatics (Please scroll down to read more about the project descriptions
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will