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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
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opportunity to join the ERC-funded project “ALPS - AI-based Learning for Physical Simulation”. Expected start date and duration of employment These are 1–year positions from 1 May 2026 or as soon possible. Job
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key agroecosystem variables. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and
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polar orbit, passing near the poles about 15 times per day and regularly observing the CIFAR study region. Its payload - two optical cameras, a thermal camera, and onboard machine-learning capabilities
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collaborative work environment, with regular scientific exchange and knowledge-sharing that helps lab members learn from each other and move projects forward efficiently. Read more:Peter Zeller What we offer
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The Daasbjerg research group at the Department of Chemistry, Aarhus University, is seeking a candidate for a 31-month postdoctoral position. This position focuses on AI/machine learning to develop a
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, didactics and learning, with approximately 240 full-time researchers, including 80 PhD students, and 4,500 Bachelor’s and Master’s degree students. The school’s activities are characterised by a high degree
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Research Focus We are offering a Postdoctoral position in graph machine learning, algorithms, and graph management with particular focus on: Modeling real-world spatio-temporal energy networks Developing
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-constrained machine-learning (ML) models in simulations of turbulent flows. You are expected to contribute to research and development in data-driven methodologies for turbulence modeling in LES (i.e., wall and
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you will teach and supervise students at Bachelor’s, Master’s and PhD level and carry out research of the highest international standards in the fields covered by The TrygFonden’s Centre for Child