14 machine-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions at Aalborg University
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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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are looking for candidates interested in developing new machine learning methods for medical image analysis, with a particular focus in anomaly detection and unsupervised learning. In this position, you will
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studying how wireless sensing and AI interact in real systems. The work will be carried out in close collaboration with researchers in wireless communications, sensing, machine learning, and robotics, with
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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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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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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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focuses on the development of secure and trustworthy AI for resource-constrained embedded systems. The research will investigate how machine learning models can be designed and deployed efficiently
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collaboration with a leading architectural firm. The candidate is expected to publish in leading Human-Computer Interaction venues. Your competencies You hold a master’s degree in human-computer interaction
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data sources (e.g., registry data, surveys, and organisations). Your competencies Digital methods such as machine learning based classification, computational text analysis, network analysis, web