220 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" "University of St" Postdoctoral positions in Denmark
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. The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background. Apply online https://fa-eosd-saasfaprod1
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Lund Andersen (ulrik.andersen@fysik.dtu.dk ). You can read more about DTU Physics at https://physics.dtu.dk . If you are applying from abroad, you may find useful information on working 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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employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human
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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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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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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