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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 days ago
-adaptive systems. We focus particularly on two properties: self-healing and self-optimization. With self-healing, we aim to study and adapt data mining and machine learning solutions to the design and
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measurement techniques and PIV. Familiarity with optics, lasers, image processing and statistical data analysis. Familiarity with flow modelling techniques (CFD) or machine learning for fluid flows. Aptitude
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developing learning-based perceptive approaches. You will develop learning and/or optimization based approaches to multi-robot path and motion planning and coordination, integrating multi-modal perception and
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staff position within a Research Infrastructure? No Offer Description Activities and context The Post-Doctoral researcher will focus on the numerical simulation and optimization of supersonic separators
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Description Job description Game theory is rapidly gaining traction in several engineering applications as the natural framework for multi-agent decision making. Yet, unlike optimization, game theory has
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optimization models. Investigate how tabular foundation models can support energy-system modelling and optimization, including applications such as prediction, surrogate modelling, uncertainty quantification
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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-Lab in Neuchâtel, within an international and multidisciplinary research environment with strong links to the photovoltaic industry. Main duties and responsibilities You will develop and optimize PV
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to develop, optimize and apply advanced mass spectrometry approaches for the structural and molecular characterization of ARDCs, and to analyze and interpret the resulting data. - Develop and optimize mass
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with national quantum strategies, such as Canada's National Quantum Strategy. The recruited candidate will participate in a Franco-Canadian collaboration focused on the study and optimization