214 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" "St" Postdoctoral positions in Denmark
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includes the following tasks: Develop computer-aided design software for modular construction of switchable RNA nanostructures. Develop databases for RNA modules for automated building of atomistic models
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includes the following tasks: Develop computer-aided design software for modular construction of switchable RNA nanostructures. Develop databases for RNA modules for automated building of atomistic models
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of the project is to map these states with Scanning Tunneling Microscopy/Spectroscopy (STM/STS) and where possible, angle-resolved photoemission spectroscopy (ARPES). Your work will focus on the spectroscopy, and
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the ability to perform complex data analyses. Has experience with implementing computer-based experiments as well as field experiments. Has professional proficiency in English, both written and spoken
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of the project is to map these states with Scanning Tunneling Microscopy/Spectroscopy (STM/STS) and where possible, angle-resolved photoemission spectroscopy (ARPES). Your work will focus on the spectroscopy, and
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grasslands and evaluation of land-use intensity, Expertise in classification with machine-learning methods, statistics, spatial analysis and land-use modeling, Experience and interest in conducting fieldwork
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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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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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staff office (ISO) https://www.sdu.dk/en/om-sdu/job-sdu/international-staff For the right candidate, there will be possibilities to influence the project and develop new project ideas within the project
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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