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and distribution of the above-mentioned microbes in oxygen-depleted environments Identification of the enzymes catalyzing the NO-dismutation reaction in AOA. Exploration of the physiological adaptations
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electricity price signals, demand-response mechanisms, and time-of-use optimization. AI-Driven Optimization using Reinforcement Learning: Apply RL algorithms to develop and train agents that optimize power
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-based topology optimisation and de-homogenisation Adaptive meshing algorithms for topology optimization PDE-driven topology optimisation methods Research fund application Collaboration with industrial
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the loop and using active learning to determine which demonstrations to collect. The candidate would work on both projects and be responsible for: Implementing AI and probabilistic ML algorithms Development
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(entities) given the rules and the rules given the molecules. The aim of this project is to develop a theory and accompanying algorithms to decide if an abstract system can be instantiated by a concrete
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programming Creating their own mechanical designs, implement and test them accordingly, Implementation of control algorithms on physical experiments. In addition, the candidates are expected to contribute with
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research is organized into five research groups that focus on specific, yet still diverse disciplines and biological focus areas. In addition, the Department has approximately 300 students distributed across
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of assignments may occur to a limited degree. The faculty determines the distribution of the various assignments. The weighting of the different assignments may vary over time. Employment will be in accordance
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on robotics, biomedical sensor and AI algorithm for cancer diagnosis. This project aims to develop a miniaturized robot and bio-sensor for on-site laryngeal cancer diagnosis. The candidate can contribute to one