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Field
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research on the effects of artificial intelligence (AI) on productivity and labour markets, combining micro-level causal inference with structural economic modelling. Subject area The subject area for
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basement structures and their role in Paleoproterozoic mineral system development in northern Fennoscandia, funded by the CAMM-CRM research initiative at LTU. Northern Norrbotten hosts numerous critical and
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used for a sustainable societal development. Project description This PhD position is part of the research project INHERIT – Geological inheritance of Archaean basement structures and their role in
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interdisciplinarity: it combines both, experimental and theoretical expertise, spanning from the investigation of surface plasmons and the design of nano-structured catalyst materials to density functional theory
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construction materials and materials from renewable feedstocks. Within and across these areas, we develop new materials, processes and analytical methods that enable advances in technology, industry and
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. Key tasks include sample preparation, extraction, and HRMS analysis, as well as processing large datasets involving feature detection, annotation, structural elucidation, and trend analysis
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collaboration with Volvo Construction Equipment, Epiroc, Boliden, Retenua, and Örebro University. The project sets out to develop multimodal, failure-resilient and trustworthy AI methods for autonomous navigation
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areas of chemistry such as analytical chemistry, physical chemistry, materials chemistry, inorganic and structural chemistry and organic chemistry. The research projects are many from theory to experiment
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biology platform https://www.scilifelab.se/units/structural-proteomics/ The unit provides access to cutting-edge equipment and expertise, for the analysis of protein interactions and conformational dynamics
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to sport and companion animals, laboratory animals, and wild animals. The department's researchers work on the entire scale, from molecular mechanisms and microbiology to the structure, function, and