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closely with a co-supervisor at the Division of Material and Computational Mechanics. The NEST-WISE project offers a vibrant collaborative environment and close interaction with academic and industrial
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This PhD position is part of the WASP-WISE NEST project RAM³ – a multidisciplinary research effort at the intersection of machine learning and materials science. The project brings together PhD
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: Master’s degree in biomedicine or biostatistics. Doctor of medicine degree with clinical practice experience. Certified training in R and Python software. Documented experience using machine learning and
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the opportunity to pursue PhD studies in Computing Science for four years, with the goal of achieving the degree of Doctor in Computing Science. While the position is mainly devoted to PhD studies (at least 80% of
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in Computing Science for four years, with the goal of achieving the degree of Doctor of Philosophy in Computing Science. While the position is mainly devoted to PhD studies (at least 80% of the time
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environments. Calculation of detector response for a number of different radiation-sensitive materials and commercial handheld detectors Validating measurements in representative geometries Testing and
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has been awarded, however, duties of this kind may not comprise more than 20 per cent of a full-time post. The researchers and teachers at the Faculty are expected to contribute to a dynamic research
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Skogar is one of the largest forest owners in Sweden. We produce raw material from forests. Our vision is to create longterm benefits from the forests, by contributing to biodiversity conservation
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development of HCFs requires fundamental understanding of light-guidance principles as well as material properties of extremely thin silica membranes. In this project, you as a PhD candidate will carry out
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to construction processes, policies, or material flows. Familiarity with research or practice at the intersection of building production methods, circular business models, and sustainability transitions. Experience