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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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numerical simulation of models for magnetised fluids. About us This position sits right between two research groups at Chalmers: the Plasma Theory group at the Department of Physics and the Geometry and
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University of Technology , where you will develop explainable AI models for personalized treatment planning in sports medicine and orthopaedics. You will work in a highly interdisciplinary environment
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formulations as complementary model systems. Integrate experimental work with spin-diffusion modeling and other complementary techniques. Collaborate actively with AstraZeneca (model systems and analytical input
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explainable AI models for personalized treatment planning in sports medicine and orthopaedics. You will work in a highly interdisciplinary environment, collaborating with leading experts in AI, mathematics
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on two main lines of research. The first concerns the modeling of general dark matter–electron interactions in detector materials. This will be achieved by combining methods from particle and solid state
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modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an innovative startup partner. You will be
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Are you passionate about pushing the boundaries of medical research? Join us at Chalmers University of Technology to explore how advanced models can transform the way we study treatments. We
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to measure and model technological deployment and to identify the role of policies in accelerating and/or re-accelerating the growth of low-carbon technologies. The interdisciplinary post-doc position requires