269 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" research jobs in Denmark
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read more about the section of Plasma Physics and Fusion Energy at https://physics.dtu.dk/research/sections/ppfe . If you are applying from abroad, you may find useful information on working in Denmark
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Professor Martijn Wubs (mwubs@dtu.dk ), Dr. Jake Iles-Smith (jake.iles-smith@sheffield.ac.uk ) You can read more about the Department of Electrical and Photonics Engineering at https://electro.dtu.dk
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obtained from Senior Researcher Bjarke Eltard Larsen , https://orbit.dtu.dk/en/persons/bjarke-eltard-larsen . You can read more about Department of Civil and Mechanical Engineering at www.construct.dtu.dk
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initiatives, as well as a wide range of research-related tasks such as qualitative data collection and analysis as well as writing academic publications. More information on “Digging for the Climate”: https
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Do you want to be part of a young, dynamic research group working on designing the next generation of sustainable energy materials using computational chemistry and machine learning? And do you see
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, electrical engineering, etc. Prior experience in (1) image processing, particularly for radiographic and computed tomographic data as well as mesh-type data, and (2) machine learning, particularly deep
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Research Assistant in Physical Computing and Wearables at the Department of Computer Science, Aar...
research is at the cutting edge of Human-Computer Interaction (HCI), personal fabrication, and physical user interfaces. As a research assistant, you will support our research team on implementing a novel
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the project based on your interests and in collaboration with a leading architectural firm. The candidate is expected to publish in leading Human-Computer Interaction venues. Your competencies You hold a PhD
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, semiparametric inference), and ideally experience with high-dimensional econometrics, machine learning, or advanced causal inference methods. Demonstrate the ability and motivation to pursue independent research
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qualifications include: Ph.D. in Computer Science, Computer Engineering, Electrical Engineering or a related field; Strong background in Deep Learning (e.g., Transformers, foundation models); Strong programming