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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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quality modelling, with focus on Knowledge-Guided Machine Learning. The position is a rewarding opportunity to be integrated in an excellent freshwater group. The department’s research and advisory
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The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to strengthen our research on image recognition, computer vision and deep learning applied
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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. Science Advances (2024). https://doi.org/10.1126/sciadv.adk1250 Your qualifications: Required qualifications: Applicants must hold a PhD degree in computer science, bioinformatics or similar. The applicant
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includes the following tasks: Develop computer-aided design software for modular construction of switchable RNA nanostructures. Develop databases for RNA modules for automated building of atomistic models
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of archetypical mitigation pathways with their differential deployments of GGR and SRM, and 6) Policy options and governance. Qualification requirements Applicants for a postdoctoral position hold a PhD degree in
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close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
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. Your competences You have academic qualifications at PhD level. Candidates can have a background in a (bio)medical discipline (incl. medicine or dentistry), medical physics, computer/data science
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experience in electromicrobiology/MFC who are motivated to engage with complex anaerobic syntrophic systems are particularly encouraged to apply. Qualifications PhD in microbiology, bioelectrochemistry