30 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" positions at University of Copenhagen in Denmark
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data management and machine learning is also preferred. An interest in energy system topics such as the green transition, sustainable energy systems, digital energetics etc. is preferred. Experience
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supervision and training of research fellows and other staff. The successful applicant must also teach, supervise, prepare and participate in examinations, and fulfill other tasks requested by the Department
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project, should contact Principal Investigator prof. Mikkel Bille, mbille@hum.ku.dk , phone +45 35329480 Link to the department’s website: https://saxoinstitute.ku.dk Introduction PhD studies consist
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analysis and biomedical data analysis, with demonstrated experience in organ segmentation from medical images, using both traditional and machine learning–based methods, and creation of large segmentation
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Attend PhD courses Write scientific articles and your PhD thesis Teach and disseminate your research To stay at an external research institution for a few months, preferably abroad Work for the department
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here: https://nexs.ku.dk/english/research/nutrition-health/lifecourse-nutrition-and-health/ Your job As postdoc you would play a key role in the PREPARE-CHILD study (https://nexs.ku.dk/forskning
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assessment database: https://ufm.dk/en/education/recognition-and-transparency/find-assessments/assessment-database . Please note that we might ask you to obtain an assessment of your education performed by
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assessment work has been completed each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself. You can read about the recruitment process at https
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optoelectronics and cryogenic device platforms in the context of artificial neural networks and neuromorphics. Information on the department can be found at: https://qdev.nbi.ku.dk/ Our research Our group conducts
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Analysis (CADA), which leverages the combined analytical efforts at the Department. Further information on CADA, as well as the Department and a description of the new research vision can be found at: https