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stocks in the future. The position is suited for a candidate with a strong interest in environmental and climate-related issues, a solid foundation in quantitative methods such as mathematics, statistics
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perspectives contribute to the development of new knowledge. About the research project Most research on environmental exposure and health still estimates exposure based on people's residential location. However
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the capabilities of today's state-of-the-art methods to extracting a richer set of material characteristics from piled materials. The position is associated with the Robot Navigation and Perception Lab (https
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. Plant science/ecology, especially related to forest ecosystems. Computer programming. Data analysis (machine learning, statistics, numerical analysis, time-series analysis, etc.). Quantitative methods in
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chain, ranging from synthesis, cell assembly, characterization, modeling to scaled-up manufacturing. The 2-year postdoctoral project Machine Learning-based Electro-Chemo-Mechanical Estimation and Control
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in the development and exploitation of X-ray and neutron methods for materials research and in, amongst other things, research into understanding the coupled electrochemo-mechanical processes of solid
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and academic disciplines. The Academy is also home to the Lindblad Studio, an experimental laboratory for sound, media, music technology and computer-assisted composition. More about the Academy
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The staff scientist will be a member of the Explainable AI (XAI) team. The XAI team’s research is focused on developing methods that allow AI systems to justify and explain their recommendations and actions
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occuring in intact soils samples, through the use of radio- and stable-isotope tracing methods, but also estimates of biogeochemical processes including C and nutrient cycling. The project will provide
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methods, provides the ideal environment for research on programming with formal guarantees — a topic of increasing practical importance. About us The Department of Computer Science and Engineering , a joint