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at the intersection of AI and advanced electron microscopy. The project focuses on developing novel self-supervised and physics-informed deep learning methods to restore and denoise Transmission
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reactions. The research at the interface of biology, chemistry and physics has resulted in two ERC awards and other high profile grants, and the group continuously publishes in high impact journals. Find more
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entry requirements Applicants should hold a Master of Science or equivalent degree in Energy Engineering, Electrical Engineering, Engineering Physics, Energy Systems, or a closely related field. The
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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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research, administration and technology and is led by Professor Anna Falk. Linked to the group is the preGMP facility, an infrastructure for process and assay development and clinical translation of cell and
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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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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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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