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research on data-driven methods for time-series tipping point prediction and their mathematical foundations, based on their expertise in fields such as mathematical sciences and mathematical engineering
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or more of the following research fields: Quantitative finance Neural Networks Financial Engineering and Risk modelling Wealth management, payment and lending AI/Machine Learning applications in financial
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control schemes, embedded-model control, data-driven approaches and robust controller synthesis; Implementation of the selected control methodologies in the high-fidelity end-to-end DFAOCS simulator; Model
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" initiatives, this field integrates automation, robotics, advanced manufacturing, integrated circuit technology, industrial engineering, complex systems modeling and optimization, and project management. It is
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, such as pulse design or numerical optimization Background in data-driven or machine-learning approaches relevant to optimal control (e.g., model learning, reinforcement learning) What you will do Take
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economic and digital transition. This research will investigate how AI can unlock new business models, accelerate SME transformation, and create high-value, export-ready enterprises driven by AI (AIDEs
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3 Mar 2026 Job Information Organisation/Company Gisèle Krysztofiak Research Field Chemistry Technology Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher
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of Time • Conduct experimental research, including characterizing mechanisms of plastic and e-waste degradation, genetic modification and engineering of model and non-model microorganisms, designing
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in technology-driven organizations as a whole. IEM offers education in the fields of engineering at the BSc, MSc and doctoral levels. Researchers at IEM are known for their broad and multidisciplinary
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models