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with privacy by developing techniques that optimize both aspects. The candidate will perform the work together with a team of postdoctoral researchers who are experts on the field and other PhD student
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Optimized Design and Control of Soft Aerial Manipulators), in collaboration with INRIA Lille Nord-Europe in France and its leading Defrost team in soft robot simulation and control, see https
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knowledge of energy system modelling or climate modelling Good knowledge of deep learning, PDEs or mathematical/numerical optimization methods Enthusiasm for challenging problems and interdisciplinary
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tools (e.g., drones, 3D mapping) for high-resolution geological mapping and rock mass quality assessment. Develop and calibrate numerical models using field data and case studies to simulate various
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Research or a related field Strong knowledge of quantitative and/or computational research methods, ideally in numerical optimization and simulation models. Proficiency in one of the major programming
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seek optimal trade-offs between compactness and performance, delivering foundational insights into the future of high-performance electric propulsion systems. Funding 3-year PhD tuition fee (for UK home
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alloys), and additive manufacturing to push performance boundaries. The research will seek optimal trade-offs between compactness and performance, delivering foundational insights into the future of high
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Your Job: develop numerical and analytical techniques to simulate and control the time dynamics of quantum technology devices implement and optimize gate operations and artificial Hamiltonians
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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linkages based on numerical simulations and to transform them into AI- and ML-ready information to develop and implement an indirect inverse optimization framework to identify microstructures that exhibit