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The Section for Electrical Energy Technology at the Department of Electrical and Computer Engineering (ECE), Aarhus University, is in a phase of rapid growth in both education and research
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are software representations of physical assets, processes, or systems. They leverage real-time data to mirror the behaviour and characteristics of their physical counterparts, enabling predictive maintenance
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experience required can be found in the Job Description document. This document will provide information of what criteria will be assessed at each stage of the recruitment process. * Please note that this is a
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Postdoctoral position for the project Human AI Collaboration: Imaginaries, Interventions, Interfaces
the stated framework of the research project (max. 1-2 pages). Please note that although the application process can be completed on the Aarhus University system without uploading publications or a teaching
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to the other phases of the research process, including in-person consumer testing of final prototypes, and to support the assessment of market trends, entry potential and societal positioning of fermented plant
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the principal SCS crystallographer. Key responsibilities will include outreach, SCXRD data collection, data processing, structure solution, and user support. To make SCS a success, the successful
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on transition metal catalysis applied to the conversion of specific plastic types to carbon capture materials. The position will focus on different catalytic processes and improving their performance
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recruitment process, please contact HR-Coordinator Maria Løvgaard Bodin, Tel.: +45 8715 3445, Email:[email protected] Place of work Aarhus BSS Department of Management Universitetsbyen 61 8000 Aarhus C Denmark
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. Collect and process environmental and insect samples for DNA sequencing. Analyse microbial communities associated with freshwater habi-tats and pollinators. Direct and support to the analysis of high
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important to integrate knowledge on processes of cognitive change and updates among individuals and in interaction with others into our data-driven computational modelling in order to understand broader