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variety of Earth surface processes. This aim is pursued through a collaboration between the Department of Sustainability and Planning and Department of Electronic Systems. The topic of this PhD position is
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mentorship. Application deadline: 27h of February 2026 at 23:59 hours local Danish time Please see the full call, including how to apply, on https://fa-eosd-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI
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! This interdisciplinary project investigates how generative AI can be incorporated into the building design and operation process. Particularly, we seek to support architects to design more sustainable buildings through
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Job Description We offer you a unique opportunity to join the PlastChain project with the aim to develop a process for chemically recycling end of life plastic waste by gasification to form syngas
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microstructures in-situ during the AM process as well as ex-situ during post-AM treatments and enable predictions of the microstructural evolution, and thus changes in properties, while AM components are in use
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project’s principal investigator, Associate Professor Lars Rohwedder, an internationally recognized expert in the areas of approximation algorithms and parameterized algorithms, see https://larsrohwedder.com
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bioelectrochemistry, a process utilizing electrochemistry to drive redox reactions catalyzed by enzymes. This technology has a large potential ranging from health (biosensors, biofuel cells) to “power-to-X
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crucial role in the modelling, design, and optimization of various systems in product and process engineering. Despite significant progress made over the decades, existing thermodynamic models and theories
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more about the department at www.es.aau.dk. The Centre for Acoustic Signal Processing Research at the Department of Electronic Systems, Section on Artifical Intelligence and Sound, Aalborg University
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nanosatellite/CubeSat constellations and to develop innovative GNSS-based sensing methods and AI models to detect a variety of Earth surface processes. This PhD position focuses on developing analytical models