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the VILLUM FONDEN. The overall aim of the project is to introduce microstructural engineering to the field of additive manufacturing (AM) of metals. This is to set the stage for optimizing metals
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to explore GNSS Reflectometry (GNSS R) as a novel, low cost, low power bistatic remote sensing technique optimized for nanosatellite platforms. GNSS R leverages signals of opportunity from existing
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-efficient, open-loop optimisation of fermentation control profiles, building on recent theoretical developments in optimal control theory, reinforcement learning and numerical methods as well as laboratory
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component, particularly magnetic components, Optimization and surrogate-modeling in Python, Integration of machine learning and numerical methods. We encourage applications from candidates with a strong
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interest in the topic, even if their background does not match every qualification listed above. Stipend 2: Data-driven modeling and optimization for efficient and secure-by-design Power Electronics (Aalborg
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on holistic understanding from regional net-zero. The PhD project is part of the Regional Energy, Carbon and Land Management initiative, focusing on optimizing energy infrastructure, land use and carbon flows
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with numerical experiments Communicate results through publications and presentations You should have a background in one or more of the following areas: Systems and Control Optimization / Operations
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and validated numerical models, to enable lightweight, reliable, cost-efficient, and sustainable novel design concepts. The PhD will also explore additively manufactured (AM) concepts with strong
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complex materials simulations. These agents will assist with setting up, executing, and optimizing electronic structure workflows, from standard ground-state Density Functional Theory (DFT) calculations
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design and integrity management of the support structure of the subsea HVDC electrode unit, supported by experimental tests and validated numerical models, to enable lightweight, reliable, cost-efficient