216 machine-learning "https:" "https:" "https:" "University of St" Postdoctoral positions in Denmark
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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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(2014). https://doi.org/10.1126/science.1253920 [2] An RNA origami robot that traps and releases a fluorescent aptamer. Science Advances (2024). https://doi.org/10.1126/sciadv.adk1250 Your qualifications
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(2014). https://doi.org/10.1126/science.1253920 [2] An RNA origami robot that traps and releases a fluorescent aptamer. Science Advances (2024). https://doi.org/10.1126/sciadv.adk1250 Your qualifications
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and 95 PhD students. The department is responsible for two educations: Molecular Biology and Molecular Medicine with a yearly uptake of 160 students in total. Please refer to http://mbg.au.dk
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inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation and maintenance prediction and integrate analytics
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protocol on certain terms of employment of academic staff at universities (only in Danish). Where to apply Website https://aau.varbi.com/en/what:job/jobID:899091/type:job/where:39/apply:1 Requirements
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Department of Management, please visit: http://mgmt.au.dk/ . Further information For further information about the position and the department, please contact Assistant Professor Gabriele Torma, email
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Postdoctoral researcher position at the Department of Animal and Veterinary Sciences, Aarhus Univ...
. Researchers in the section teach the BSc and MSc programmes in animal and veterinary science and supervise PhD students and conduct research-based public sector consultancy for national and international
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the scientific communication of research results. For non-Scandinavian candidates, an effort to learn to read, write and speak Danish is a requirement. What we offer A well-developed research infrastructure
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hold a PhD in oceanography, marine ecology, computer sciences, data sciences or similar. We expect that you have: Expert knowledge on network modelling, especially aimed at ecological applications Strong