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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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of visualization and multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240
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multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240 ECTS credits
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score (Academic) of 6.0 or more (with none of the sections scoring less than 5.0) TOEFL score of 550 or more (computer based test 213, internet based 79) Cambridge/Oxford - Advanced or Proficiency level
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the national infrastructure network SciLifeLab for Cryo-EM and cellular volume imaging, providing “state of the art” technology access for this project. Cryo electron microscopy (cryo-EM) methods provide
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SciLifeLab for Cryo-EM and cellular volume imaging, providing “state of the art” technology access for this project. Cryo electron microscopy (cryo-EM) methods provide possibilities to visualize
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focused on mass spectrometry and development of new techniques for mass spectrometry imaging and single cell mass spectrometry to reveal chemical processes of importance to biological function and
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imaging and single cell mass spectrometry to reveal chemical processes of importance to biological function and dysfunction. The research group has recently received major and prestigious grants
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to assimilate knowledge at the research level. Understanding and experience in machine learning and computer vision. Knowledge, experience, and strong interest and in AI and XR development. Knowledge and
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facilitate data sharing among actors involved in a new circular flow of flat glass. Within the project, two PhD students, one at the Department of Computer and Information Science (with computer science