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Field
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community engagement. In this role, you will: Contribute to research on ecological and spatial data for urban environments: Conducting fieldwork, data collection and analysis related to urban air quality and
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the trusting; and the situations where we are more likely to ‘outsource’ moral decisions to AI agents. By understanding this, we consider the ethical promise and pitfalls of such moral machines and how
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exceptional researchers to join our dynamic team. As a Machine Learning Researcher, you will apply advanced ML techniques to a wide range of forecasting challenges, including time series analysis, natural
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of the Discrete Choice Experiments in Mozambique and South Africa, and the analysis of the ensuing data Develop computational models of health actors’ decisions and responses to regulatory options Collaborate with
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Decision Intelligence for Supply Chain and Operations Optimization. The successful candidate will contribute to cutting-edge research at the intersection of Statistical Machine Learning and Generative
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electron microscopy analysis, Raman spectroscopy, fluid inclusion analysis, potentially appropriate petrochronological methods, and 3D geological modelling. The project will be conducted in partnership with
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on the following criteria: Knowledge in electric power engineering, power electronics, and power system analysis Experience in modelling, simulation, and experimental work Proficiency in Swedish and English, both
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that the electrolysers operate safely and reliably while fulfilling the intended specifications. The knowledge gained from the experiments will be used to determine the appropriate risk and reliability analysis
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established methods of microstructural analysis and mechanical testing with new schemes such as Acoustic Emission for non-destructive assessment of degradation and Machine Learning for development of predictive
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subprojects (SP): 1) SP1 includes desk research and case file analysis about how decisions are based on what kind of legitimations 2) SP2 unfolds how decisions are justified in-the-making via shadowing and