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. Your work will focus on developing physics-informed AI methods to enhance decision-making in design and operation of next generation thermal energy storage systems, such as latent heat TES and
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of research results in scientific journals and conferences. Qualifications: Good understanding of solid mechanics and preferably modeling of damage and/or fracture. Experience with experimental work and data
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at the University of Queensland. Work closely together with lab technicians who carry out analysis for characterization. Participate in the supervision of students and contribute to teaching activities at both
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. The approach will be validated by application to industrial production at a partner company. The position includes both theoretical and experimental work and carries project as well as academic responsibilities
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is part of SDU’s strategic effort to advance PtX technologies through experimental validation and intelligent control. The research combines hands-on laboratory work with AI-based approaches
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overall focus will be to contribute to strengthen the department’s competences within gas fermentation technology. You will work with nearby colleagues and academic partners in Denmark as well as abroad
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prepared to operate in an interdisciplinary setup. Beyond the project team and the colleagues at the Visual Analysis and Perception lab, the PhD student will be part of the Pioneer Center for AI – a large
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Job Description Are you passionate about renewable energy and eager to apply machine learning to real-world challenges? Join our research team at DTU and work on groundbreaking advancements in
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of the biggest challenges is the development of efficient, scalable, and low-noise control electronics that operate at cryogenic temperatures. This PhD project addresses this challenge by designing CMOS-based
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. The research should focus on low-power embedded systems, multimodal sensing (including wearable shoe-based platforms), and edge-cloud computing with serverless and federated learning techniques. You will work