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data combined with focussed innovation in statistical and computational methods including machine learning to advance our understanding, treatment, and prevention of human disease. Information
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organizational theory, the learning sciences, digital transformation, digital technologies, human-computer interaction, and related fields. Within the specific field, the PhD student will engage in both research
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, you will work at the intersection of polymer processing, materials science and Machine Learning to develop dynamic recipes for sustainable plastics. In a typical plastics production line, several types
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At the Faculty of Medicine, Department of Health Science and Technology, one or more PhD stipends in Human-Machine Interaction are available for appointment from October 1, 2026, or as soon as
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paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported
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DTU Management invites applications for a 3-year PhD Scholarship associated with the project “Brains in Motion: Explaining How Humans Learn and Adapt to Navigate Urban Environments Using Artificial
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paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported
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professors, two postdocs, and five PhD-students. The group focus on high-quality applied research. The current topics of interest in the group include student learning, transitions and career, teacher
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advanced analytical approaches, including deep learning and machine learning, to improve disease subtyping and risk prediction. You should have a strong willingness to learn, enjoy tackling challenging
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Engineering, Machine Learning, Applied Mathematics, or a related field. A strong academic background and interest in AI systems, embedded intelligence, edge computing, machine learning, or related areas. Strong