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PhD Scholarship in Design optimizer tool and predictive control system of a Megawatt Charging System
. • You specialize in the following topic: Development of a design optimizer tool and predictive control system of a Megawatt Charging System and local grid; • You work on projects independently
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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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Engineering, we have an open vacancy for a PhD researcher in the mechatronics research group at the campus Kortrijk. The research in our group focuses on modelling, control, sensing and optimization
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for wind turbines, with the ultimate objective of including structural health information in windfarm asset management to optimise structural lifetime consumption while guaranteeing optimal power production
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of optimization and flexible query answering reduction or enrichment because it impacts on which L-grades (and their corresponding objects) are kept into consideration for further computations. • Fusion relates
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Engineering, or equivalent. Candidates with background in operations research, systems engineering, control and optimization or in a closely related domain are strongly encouraged to apply. We offer a pleasant
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model of the ultrasound-sensitive hippocampal formation as environment. The candidate will develop surrogate models of the hippocampus to allow for more extensive optimization of the controller. Finally
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Job description Short job description We are seeking a highly motivated and talented PhD researcher in the field of mechanical and control engineering of robots. You will work on a cutting-edge
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and control, using the insights from synchronized models. A critical challenge is to realize a Digital Twin which can quantify sustainability metrics online, and optimize these by acting automatically
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. The central aim is to design intelligent systems that dynamically adapt the environment to support optimal learning conditions, based on real-time neurophysiological feedback. Key principles guiding