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deep learning, computer vision, medical image analysis or unsupervised learning is an advantage. English language skills, both written and spoken Qualification requirements PhD stipends are allocated
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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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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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PhD Scholarship in University Students’ Learning Via Digital Twins of Neutron Scattering Instruments
. Responsibilities and qualifications This PhD project will research and document students' learning outcome of engaging with digital twins of four ESS Instruments. Facilities like ESS are crucial in basic and applied
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Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position
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an international research environment spanning communication theory, networking, information theory, sensing, machine learning, and robotics. Qualification requirements PhD stipends are allocated to individuals who
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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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PhD positions in Human-Centred Artificial Intelligence The Department of Computer Science at Aalborg University invites applications for two fully funded PhD positions working with Professor Niels
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of electrolyzer technologies, digital twins, model order reduction, system identification, power electronics, model predictive control, multi-objective optimization, machine learning, renewable-energy integration