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effort at the intersection of machine learning and applied mechanics. The focus of this position is on extracting information about what a neural network has learnt in a symbolic and (human) interpretable
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of Mechanical and Aerospace Engineering and is available to UK students. The successful student will receive an annual tax free stipend set at the UKRI amount (£20,780 for 2025/26) and tuition fees will be paid
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subject see general curricula for the Board of the faculty of science and technology Qualifications To be qualified for the position, you must have a MSc degree in Electrical or Mechanical Engineering or
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of the faculty of science and technology Qualifications To be qualified for the position, you must have a MSc degree in Electrical or Mechanical Engineering or Computer Science or Agricultural engineering or
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at the Division of Transport, Energy and Environment at Chalmers University of Technology, Department of Mechanics and Maritime Sciences . You will join an interdisciplinary team with Ida-Maja Hassellöv, Lars
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Environment at Chalmers University of Technology, Department of Mechanics and Maritime Sciences . You will be joining an interdisciplinary team with Ida-Maja Hassellöv and external collaborators Amanda Nylund
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally
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are available in the Centre of Infrastructural Monitoring and Protection (CIMP), School of Civil and Mechanical Engineering at Curtin University, Australia. The successful candidates will work with Associate
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the molecular mechanisms underlying rare diseases and autoimmune disorders. Through innovative approaches such as gene editing and cell therapy, we aim to develop novel therapeutic strategies to combat
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the need for sustainability to achieve Net-Zero goals. Cyber-Physical Systems (CPS) integrate machines, robots, and AGVs, but challenges like mechanical wear and electronic errors pose risks to efficiency