31 machine-learning-"https:"-"https:"-"https:"-"Linnaeus-University" PhD positions at Aalborg University in Denmark
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for PhD stipends or integrated stipends in the field of Machine Learning for Intelligent Hearing
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a PhD stipend in the field of Safe Learning Based Control for Autonomous Robots in Dynamic
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At the Technical Faculty of IT and Design, Department of Sustainability and Planning, a position as a PhD student in Problem-Based Learning (PBL) and Sustainable Education at the Aalborg Centre
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Engineering, Science and Systems (DESS) research group focuses on data-intensive systems, spatio-temporal data management, data analytics, and applications of machine learning, with applications in digital energy and
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This PhD explores light estimation and synthetic relighting of real scenes by combining generative deep learning with computer graphics. It aims to reduce issues such as hallucinations and temporal
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infrastructure. The research will investigate how machine learning models can be designed and deployed efficiently on constrained hardware platforms while supporting the reliability and security requirements
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combines multimodal data sources, physical models, and advanced machine learning to create new forecasting and communication tools. The lab is looking for candidates for the following two stipends: Stipend 1
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candidate is expected to publish in leading Human-Computer Interaction venues. Your competencies You hold a master’s degree in human-computer interaction, computer science, interaction design, applied
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Engineering, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field) • Strong programming skills (e.g., Python) • Strong skills in machine learning, deep learning and modern
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Do you want to be part of a young, dynamic research group working on designing the next generation of sustainable energy materials using computational chemistry and machine learning? And do you see