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of protein design pipeline knowledge of computational pipelines for protein design an advantage. Extended knowledge of inorganic and organic chemistry relevant to hybrid material design an advantage
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for molecular dynamics (MD), slashing computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with
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applied to sustainable materials. About us Stimulated by major needs and challenges in science and a sustainable society, the ambition of the Department of Physics is to foster a creative environment for
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Science (CMPS). You will be part of an ambitious and dynamic research team exploring new frontiers in programmable protein–semiconductor materials, combining computational modeling, high-throughput
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outreach. We provide a competitive advantage by linking our top-level international and interdisciplinary academic performance in the areas of material science, nanotechnology and energy research with world
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at the Division of Materials and Manufacture, which belong to the Department of Industrial and Materials Science. The Department of Industrial and Materials Science shares knowledge and their vision of technical
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organic chemistry relevant to hybrid material design an advantage. Significant experience of developing deep learning methods using computational frameworks such as PyTorch, TensorFlow etc an advantage
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organic chemistry relevant to hybrid material design an advantage. Significant experience of developing deep learning methods using computational frameworks such as PyTorch, TensorFlow etc an advantage
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-state chemistry, materials science, condensed matter physics, or related fields, awarded no more than three years prior to the application deadline. Strong background in inorganic solid-state chemistry
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8 Nov 2025 Job Information Organisation/Company Uppsala universitet Department Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Arts, Department of Archaeology