196 evolution "https:" "https:" "https:" "https:" "University of Cambridge" PhD positions in Denmark
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(CAM) . CLINDA aims to conduct independent research in the development, application, and implementation of data infrastructures for AI-based decision support tools and is rapidly growing with currently
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prediction outputs. The first PhD will work on data fusion, feature extraction, and model development ranging from baseline approaches (e.g., gradient boosting) to deep learning architectures. The work also
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Job Description The Department of Energy Conversion and Storage, Technical University of Denmark (DTU), invites applications for a PhD scholarship in the development of all solid-state Li-metal
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evolution in Denmark, and potential challenges and opportunities. You will contribute to these analyses but also have freedom to pursue original ideas, which can then shape the thematic chapters
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with national and international academic and industrial partners in microelectronics, photonics, and quantum technologies. Strong support for professional development through the Lecturer Training
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the mechanisms underlying inflammatory diseases and their role in tissue damage and disease development. The research is characterized by close integration of basic and translational approaches, as well as well
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development, biomass availability, and sector coupling is experiencing significant growth. The group combines techno-economic modelling, system optimization, and infrastructure planning to address real-world
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the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives
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they lead to electrochemical failures under low and high voltage bias. The project will also include the development of secondary electrochemical models as digital twins. This PhD project is part of CreCon
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year before the position expires, you will be offered an interview to clarify your future career. The PhD research will focus on the development of AI models for analysis of prehospital ECGs, with