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amplifier performance. By combining advanced device measurements, empirical modeling, and power amplifier design, this project will generate new insights into the material, process, and design factors
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Join us to pioneer next-generation generative models that accelerate molecular dynamics. We seek a postdoctoral researcher to develop AI surrogates for molecular dynamics (MD), slashing
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knowledge base. Main responsibilities include: Conduct benchmarking and further development of risk assessment models and components. Investigate the reliability of accident data, including cross-validation
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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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to emerging digital technologies Interplay between technology development and business model evolution - how advancements in technologies reshape value creation and value capture, necessitating continous
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the models and measurement methods. The position is based at the Division of Transport, Energy and Environment within the Department of Mechanics and Maritime Sciences . The division conducts
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nitride (hBN)-based thermal interface material in this project. The hBN material offers high thermal transfer performance while providing electrical insulation for AI booted electronics and battery cooling
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us The position is based in the Division of Materials and Manufacture at the Department of Industrial and Materials Science (IMS), Chalmers University of Technology. Our division conducts cutting
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abundant side streams into high-value bio-based materials, contributing directly to the circular bioeconomy. You’ll work with cutting-edge bioprocessing tools, collaborate with leading European partners, and