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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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. 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
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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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student to work with SERS for monitoring infections in wound samples. We will target the detection of bacteria in wound samples. We offer a highly creative, collaborative, and ambitious work environment
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-situ spectroscopic and microscopic methods, including XRD, Raman spectroscopy, TEM, and XPS. Evaluating catalytic performance for various electrochemical reactions, such as the oxygen reduction reaction
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from related projects at DTU-Bioengineering (https://biocat.ncsu.edu/) and researchers from the private sector. Overall, you will become part of a high-energy, supportive, and inclusive work environment
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joining the division of Geodesy and Earth Observations, which is one of the six divisions at DTU Space. You will work in close collaboration with colleagues at both DTU and with academic partners
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meteorological phenomena across difference scales, that impact wind energy, and vice versa. Our research is needed in the process of planning, designing, and operating wind energy installations. This can be at
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Software Defined Vehicles (SDV). The primary objective is to expand, mature, and industrialize a novel European RISC-V automotive ecosystem that enables next-generation high-performance European automotive
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. You will work under the supervision of Prof. Francisco C. Pereira, Assoc. Prof. Carlos Lima Azevedo (DTU), Dr. Biagio Ciuffo and Dr. Georgios Fontaras (JRC). You will work on research focused