27 learning-"https:" "https:" "https:" "https:" "https:" "https:" PhD positions in Denmark
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PhD Scholarship in Development of Cement-Free Living Building Materials for Sustainable Construction
commitment to research excellence Possess the ability to work independently, take initiative, and drive research activities forward Show adaptability and a willingness to learn new concepts, techniques, and
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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
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Other relevant professional activities Curious mind-set with a strong interest in enzyme structure and function An ability to learn new skills An ability to interact professionally with other scientists
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, with the earliest start date 1 November, 2026. Further details and application instructions are available at: https://math.au.dk/en/about/vacancies/phd The webpage includes brief subject descriptions and
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/augmented/extended (VR/AR/XR) environments to support learning of scientific concepts and practices at the university-level. The main aim of this work package is to investigate how such cutting-edge
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rapidly digitalising society and contributes to the development of sustainable, inclusive, and pluri-/multilingual ecosystems across Europe. More information may be found on the MultiLAwa home page https
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-Facilitated Blended Interaction Learning Spaces: Project framework A persistent challenge in higher education is the asymmetry between learning formats: lecture-based teaching offers students clear pathways
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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
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, ethnography, and policy studies. Further description of the project can be found here: https://dff.dk/en/our-funded-projects/meet-the-researchers/research-leaders/eksterne-personer-en/research-leaders-2026
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, mathematics, biology, and epidemiology, developing and applying novel statistical methods and deep learning approaches for global health challenges. The group’s research spans disease modelling, genomic