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subsurface and internal temperature distributions. Semi-destructive approaches, such as embedding thermocouples by drilling holes, can provide internal data but often disrupt the process, alter the thermal
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toward safe AI control systems. The candidate will be part of the Distributed, Embedded and Distributed Systems research group: https://www.cs.aau.dk/research/distributed-embedded-intelligent-systems
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experience with algorithms relevant to computational biology documented programming skills, e.g. in Python and R very good communication and organizational skills with the ability to work to timelines, both
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consumption, create energy labels for algorithm scalability, and guide implementers in choosing more efficient algorithms. Ready to make AI more sustainable? Apply now! The goal of your PhD project is to
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approach could resolve this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat
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research lines. Research line 1: "Digital twinning for 3D network optimization" focuses on developing distributed digital twin architectures and mechanisms for distributed network optimization in networks
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well as developing solution algorithms applying mathematical and computational approaches. The group has a particular focus on automated decision making in autonomous cyber-physical systems. Autonomous systems and
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build the sustainable companies and societies of the future. Pervasive and Mobile Computing (PMC) research subject addresses fundamental challenges in distributed systems and mobile networks, enabling
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build the sustainable companies and societies of the future. Pervasive and Mobile Computing (PMC) research subject addresses fundamental challenges in distributed systems and mobile networks, enabling
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, distributed ledgers) Desirable: Experience with generative AI (e.g. LLMs) Interest in Human-Computer Interaction Interest in privacy enhancing technologies (PETs) Other: Experience in presenting or preparing