16 parallel-computing-numerical-methods Postdoctoral positions at Aalborg University in Denmark
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At the Faculty of Medicine, Department of Health Science and Technology, a position as Postdoc in Medical Informatics and Image Analysis Group is open for appointment from November 1, 2025 or soon
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Graph Machine Learning and Graph Data Management At Section for DATA, Department of Computer Science, Aalborg University, a postdoc position is available. The project is funded by a Novo Nordisk
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with 15 researchers at various career levels with expertise within molecular methods development, bioinformatics and machine learning. Furthermore, the position will be anchored in the Center
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level the candidate is expected to be able to communicate in Danish. Who we are In the Automation & Control section, we focus on developing mathematical and computational methods for modeling, estimation
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Metagenomics group with 15 researchers at various career levels with expertise within molecular methods development, bioinformatics and machine learning. Furthermore, the position will be anchored in the Center
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. The topic of this Postdoc position is the development of data-driven methods to estimate river streamflowusingsatellitealtimetry. Particularly, the Postdoc willexplore hybrid deep learning models
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to join our team working on next-generation speech enhancement technologies. The project explores innovative approaches that move beyond traditional reference-based methods, leveraging optimal transport and
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characterization in complex in-situ environments. The key responsibility of the position is to develop post-processing methods to extra essential features from the collected measurement data despite drone positional
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scale. Furthermore, the work will include biomass extraction and fractionation using novel green extraction methods as well as detailed biomass chemical characterization using spectrophotometric bioassays
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. The Postdoc will conduct research on methods to enhance the performance, safety, and lifetime of lithium-ion batteries by integrating physics-based modeling with data-driven approaches. The work will include