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by combining state-of-the-art computer simulations, physical experiments, and clinical studies in radiology departments at the hospitals in the region. You will work in a multi-disciplinary team and
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to automate the process of species classification. However, there are still several methodologies that need to be developed to integrate these models into a functioning workflow for ecologists. In this 4-year
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goal is to integrate physical priors — including periodicity, symmetry, and long-range correlations — directly into the learning process to achieve more robust, interpretable, and scientifically
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at the time of application. More about selection criteria and the process can be found in the general syllabus for the subject, see https://mau.se/en/research/doctoral-studies/https://mau.se/forskning
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with respect to R&D work related to TS coatings. The core focus of the group's research revolves around unravelling the fundamental correlations between process parameters, coating microstructure, and
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are affected by chemical composition and crystal structure. For example, it studies how the process parameters and synthesis methods affect material properties. An important area is new magnetic materials based
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adaptation and high-versus low intensity forestry. We use empirical and process based modelling, with input data from the National Forest Inventory and long-term experiments. Qualifications: The applicant
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purposes, addressing issues on climate change adaptation and high-versus low intensity forestry. We use empirical and process based modelling, with input data from the National Forest Inventory and long-term
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Applications are welcome from candidates with an M.Sc. degree (or equivalent, including candidates who are about to complete their degrees) in materials science, chemistry, physics, or related fields. In
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from candidates with an M.Sc. degree (or equivalent, including candidates who are about to complete their degrees) in materials science, chemistry, physics, or related fields. In addition to the above