16 condition-monitoring-machine-learning Postdoctoral positions at Aarhus University in Denmark
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Monitoring and Conservation Genetics. Expected start date and duration of employment This is a 2–year position from 1 February 2026 or as soon possible. Job description The position will focus on developing
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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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collaboration between the Department of Electrical and Computer Engineering and the Novo Nordisk Foundation CO2 research center, Aarhus University, we aim to address this opportunity by developing digital twins
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: https://ece.au.dk What we offer The Department of Electrical and Computer Engineering offers: An exciting opportunity to work on cutting-edge research in IoT systems and critical infrastructure monitoring
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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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the way they orchestrate multiple voices and create coherence in texts – all of which are pivotal for literacy learning. Besides much-needed empirical insights, we expect to enrich the theoretical concepts
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: Operator Algebras, Machine Learning, Analytic Number Theory, Automorphic Forms and Representation Theory Appl Deadline: 2025/10/10 11:59PM (posted 2025/09/10, listed until 2025/10/10) Position Description
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Researcher (R1) Positions Postdoc Positions Country Denmark Application Deadline 18 Dec 2025 - 23:59 (Europe/Copenhagen) Type of Contract Temporary Job Status Full-time Hours Per Week 37 Offer Starting Date 1
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. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and process-based radiative transfer models
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monitoring of neurological diseases. While current diagnostic methods rely heavily on bulk measurements (e.g., cytokines, cell counts), they fail to capture the dynamic and heterogeneous nature of central