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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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Danish time Please see the full call, including how to apply, on www.sdu.dk
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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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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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hours local Danish time Research project Obesity is a major risk factor for a range of metabolic complications, including metabolic-associated steatotic liver disease (MASLD) and coronary artery disease
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parameters by trial-and-error, leading to a time consuming sub-optimal selection. In the domain of high precision machining, tools are prematurely discarded to avoid the risk of costly non-conformities
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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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timely change in operation conditions to avoid the escalation of degradation will be key to ensure long operational life of SOEC’s. Responsibilities The candidate(s) will work on developing advanced and
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pylori, an ancient inhabitant of the human stomach, with a rapidly declining prevalence. The organoid work will complement our other approaches, using mouse infection experiments and screening of clinical