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recrystallization and control nucleation for biomedical applications in e.g. heart and kidney cryopreservation. Where to apply Website https://www.academictransfer.com/en/jobs/359905/phd-in-de-novo-design-of-ice-bi
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- and risk optimal installation and operation of offshore wind farms depend on accurate forecasts and predictions of environmental conditions and response of vessel and auxiliary systems. The focus
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This exciting opportunity is based within the Mechanical and Aerospace Systems (MAS) Research Group at Faculty of Engineering which conducts cutting-edge research into robotics, control, and
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First Look at Operational RAN Updates and Their Impact on Carrier Traffic Demands and Prediction, IEEE INFOCOM 2026 [2] M. Jabbari, A. Duttagupta, C. Fiandrino, L. Bonati, S. D’Oro, M. Polese, M. Fiore, T
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on the combination of Reinforcement Learning (RL) and Model Predictive Control (MPC). It will build up upon the work done at ITK on the topic. Several research focuses are considered: verification pathways in RLMPC
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on the structure and dynamics of ring polymers in different topological environments, providing experimental evidence for phenomena predicted by theory and computer simulations. Small-angle neutron scattering (SANS
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Institut National des Sciences Appliquées de Lyon | Villeurbanne, Rhone Alpes | France | 16 days ago
solutions for vibration and noise control in lightweight structures (https://cordis.europa.eu/project/id/101227712 ). The project focuses on the development of Acoustic Black Hole (ABH) technologies
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: (1) automated reconstruction of a visual and geometrical 4D Digital Twin based on visual computing; (2) usage of information from digital imaging techniques for estimation and prediction of current and
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with over 60 companies. The research will focus on the combination of Reinforcement Learning (RL) and Model Predictive Control (MPC). It will build up upon the work done at ITK on the topic. Several
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MRI measurements can be translated into meaningful input for predicting optimal sensor phase configurations and feedback control; Identify pathways towards the integration of domain knowledge about MRI