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optimization models and algorithms to address the above questions. Given the uncertainties involved in food supply chains, we prefer candidates who have a background in (stochastic) optimization methods (e.g
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position for candidates interested in interpretable AI, stochastic optimal control, deep learning and high-impact research in sustainable mobility. About us The position is located at the Systems and Control
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high-quality research on interpretable and learning-based stochastic optimal control for over-actuated electric vehicles, with a focus on ensuring robustness and fail-safe operation. You will: - Develop
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on Friday 15 August 2025 Reference: IM-1930 Position: Doctoral Candidate #5 (DC 5) Project: Safe and legal operation of robots in agricultural environments Host Institution: Harper Adams University
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PhD). Tasks: The successful candidate is required to conduct research on a topic in probability theory (e. g. stochastic processes / stochastic analysis) and its applications. You support the institute
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Prof. dr. Herman Monsuur (Netherlands Defence Academy) - H.Monsuur@mindef.nl For questions about the application procedure please contact: Lindsey Pijpers (PhD Officer) – doctoraloffice@ese.eur.nl
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laboratory-based skills Application Procedure Informal enquiries are encouraged and should be addressed to Prof Daniel Eakins (daniel.eakins@eng.ox.ac.uk). Candidates must submit a graduate application form
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. Your work will focus on developing physics-informed AI methods to enhance decision-making in design and operation of next generation thermal energy storage systems, such as latent heat TES and
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(if existing) with respect to: Optical flow measurement methods, e.g. PIV. Methods to model stochastic processes and/or spatio-temporal dynamics. Develop or adapt models of turbulent fluid flows Dynamical
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MMF/Nexus pipeline and the stochastic Bayesian Bisous method. To improve, extend and deepen the analysis to a full dynamical inventory, a major incentive for the project is the application and