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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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Are you interested in developing computational tools to understand the detailed mechanical behaviour of multi-phase materials? Then this PhD position at Chalmers University of Technology might be
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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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Master’s degree in Applied Mechanics, Mechanical Engineering, or a closely related field. Strong knowledge of fluid mechanics, CFD, turbulence modelling, and structural mechanics. Understanding
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safety. You will work on developing control algorithms all the way to performance assessment in test vehicles. The project combines theoretical aspects of control algorithms, experimental design, and
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our research team for addressing a timely societally relevant problem. Project overview The aim is to unravel the mechanisms, and time scales involved at particle scale, for the formation and failure
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range of backgrounds, perspectives, and life experiences. We believe that this variety drives excellence and innovation, strengthening our ability to lead in science and technology. We are committed
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of biomolecular condensates in immune cell activation and identify the mechanisms controlling the expression of immunoglobulin transcripts. Using both experimental molecular and cellular biology methods and