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the frame of the FNR-CORE supported project OPTMONITOR (Optimal Monitoring and Coupled Modeling for Climate-Driven Landslide Risk Detection) at the University of Luxembourg (Faculty of Science, Technology and
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tentatively entitled “Optimal e-bus charging infrastructure and fleet management considering Vehicle-to-Grid (V2G) connectivity, local renewable energy and dynamic pricing”, and will address “to what extent V2G
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to particle separation systems. · Optimize the design of particle-handling systems for the space environment, including the development of robust design criteria · Couple physics-based models and
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, specifically methods that combine machine learning and optimization with physics-based simulation and/or physical constraints and translate these methods into impactful industrial applications. The position is
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, the Optimized AI team focuses on computing techniques to scale up a wide range of AI approaches and drive the SW-HW-Technology co-optimization. We analyze and implement AI models and software architectures while
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entitled “Non‑Alcoholic Beer Production Using Enzymatic Treatment of Barley Wort for Optimized Fermentation with Non‑Saccharomyces Yeasts.” The primary objective of this project is to demonstrate
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, environmental disturbances, aging effects, and calibration issues, which may compromise monitoring and optimization strategies. The objective of this PhD project is to develop methods to ensure reliable
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University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture | Croatia | 17 days ago
Engineering and Naval Architecture - Ivana Lucica 5, Zagreb, Croatia indicating „APPLICATION“. Project name: AI-Driven Digital Twin and GIS Optimization for Advanced District Heating Systems Where to apply E
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University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture | Croatia | 17 days ago
Lucica 5, Zagreb, Croatia indicating „APPLICATION“. Project name: Sustainable and Optimized Hull Maintenance Strategy for Ferries in the Adriatic Sea Where to apply E-mail zaposljavanje@fsb.hr Requirements
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implements multi-agent systems to optimize clinical decision support and patient monitoring. Rigorous testing of AI safety protocols ensures the reliability and ethical deployment of these autonomous models