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Field
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can reduce model accuracy, especially when modeling multiple processes that interact across different spatial scales. To address this, the project will develop a new class of raster data-processing
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at the Faculty of Engineering and contribute to cutting-edge research in radar systems. The radar group at BTH has extensive experience in radar research, developing signal processing algorithms for long-range
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control and reinforcement learning supported by an edge-cloud-based wireless communication environment. The doctoral student will work on data-driven theory and method development in simulation environments
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growth. The 60 doctoral students within the department are a diverse group from different nationalities, backgrounds and fields. We offer very good employment conditions, and administrative and technical
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equality, where different experiences generate conversations between people and pave the way for science, creativity and development. Therefore, we welcome applications from people with diverse backgrounds
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a long-term difference in society. Our most important assets are all the individuals whose curiosity and dedication make Uppsala University one of Sweden’s most exciting workplaces. Uppsala University
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teaching ability, including a good ability to conduct, develop and lead teaching and other educational activities on different levels and using a variety of teaching methods. An ability to supervise doctoral
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data for urban characterization. The work includes developing algorithms, performing large-scale analyses, and collaborating with partners across disciplines in remote sensing, urban studies, and climate
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of Geology in a joint and co-located organisation, the new department will strengthen the link between different research fields, develop new educational programmes and promote collaboration with society
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composition, structure, properties and production of materials – mainly metallic and ceramic – as well as application aspects. Project description The main goal of this project is to identify and develop