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. As a hydro-focused center, the WERC conducts vital projects that turn sciences and engineering into actionable solutions. By integrating machine learning, sensing technologies, and predictive modeling
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able to teach in Swedish after two years. - A completed doctoral degree in Mechanical Engineering, preferably with a focus on additive manufacturing and/or material science, or equivalent scientific
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engineering, or another related field Strong knowledge of Machine Learning theory and methods, and related Deep Learning approaches Excellent knowledge of programming in Python and scientific libraries used
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applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital
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users, thanks to the use of machine learning tools and techno-economic analyses. This project is aligned with the sustainable development goals (SDG) 7 and 10 of the United Nations, by promoting a low
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and policy. The position emphasises robust data engineering practices, reproducible analysis, and the application of statistical and machine learning methods to complex, real-world systems. Working
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statistical physics, control theory, and where appropriate, machine learning and data-driven techniques. The position offers a structured career development path within an active and ambitious research group
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manipulation tasks. We are seeking candidates with a strong background in robotics and machine learning, and demonstrated experience in two or more of the following areas: deep learning, reinforcement learning
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technology and Windows software Effective communication and organizational skills Flexibility with daily work duties Ability to lift 30 pounds Additional Information The student assistant will help in a
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of the TBM (Tunnel Boring Machine) current technology to suit the new grout. Learning, deploying, and transferring a novel risk-based, probabilistic design approach Mastering and deploying a holistic design