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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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and impacts on the marine environment. This is an opportunity for you to contribute to science-based guidance of the maritime industry in the green transition. The goal is to provide risk-based decision
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development for powder-based metal additive manufacturing (AM), covering the full value chain—from powder production and AM process development to post-processing and final components. Hosted by the Division
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students pursue their Ph.D. in a similar area, which plenty of opportunity to collaborate and learn from and with peers. About the research project This ad is for a Ph.D. student researcher that will work in
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The Department of Architecture and Civil Engineering (ACE) at Chalmers University of Technology has approximately 250 employees, encompassing a broad theoretical and practical knowledge base. In ACE, the Division
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wastewater systems. Research environment The project is based at the Division of Water Environment Technology (WET), within the Department of Architecture and Civil Engineering. You will be part of
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courses, including several master’s programmes. Learn more at: www.chalmers.se/en/departments/e2 Qualifications To qualify, you must: Hold a Master’s degree (or equivalent, 240 ECTS) in Engineering Physics
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terms The position is limited to four years, with the possibility to teach up to 20%, which extends the position to five years. Please note: Physical presence is required throughout the entire study
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Project overview Climate change and increasing flood risks pose significant challenges to urban infrastructure worldwide.While many municipalities are exploring catchment-based approaches
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tasks Contract terms The PhD positions are fully funded from start. The position is limited to four years, with the possibility to teach up to 20%, which extends the position to five years. A starting