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activities are focused on the modelling of the mechanics of structures, components, and processes along with involved materials, thereby providing mechanics-based solutions and virtual solution tools to our
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. This will be achieved by combining advanced constitutive models that capture the rate-dependent (creep and porewater pressure) response of sensitive clays with erosion models enabling system-level studies
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structural engineering. The research subject of Structural Engineering is now seeking a motivated researcher who will contribute to the science and technology of structural condition assessment, structural
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at least 30 credits must be at the advanced (master's) level. Courses in statistical analysis, quantitative methods, or mathematical modelling obtained outside these subject areas may also be included
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to advance bio-based adhesives for furniture, packaging, and wood construction products through collaborative research. Both initiatives prioritize strong collaboration with industry partners to ensure
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The doctoral student project and the duties of the doctoral student This Data Driven Life Sciences (DDLS) PhD project focuses on probabilistic models of protein structure, which can be used primarily
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research activities in stormwater management. The research is both theoretical and experimental with elements of computational technology and mathematical modelling and is based on close collaboration with
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Science with an interest in molecular and structural virology. The position at the Department of Medical Biochemistry and Biophysics at Umeå University is temporary for four years to start during spring
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Team up with up to 3 fellow Ph.D. students in the DSP-assisted Wideband & Efficient Transceivers (SWEET) project which is part of the WiTECH center to perform cutting-edge multi-disciplinary research in system and circuit design for next generation wideband radio frontends. The position allows...
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as