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to this project, including one at G2Elab. The experimental results will be obtained on models defined jointly with VALEO. Progress meetings will enable the postdoctoral researcher to follow a large-scale project
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About the ProjectProject details Self-adaptive and autonomous systems are increasingly deployed in dynamic and uncertain environments, where effective decision-making relies on accurate models
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position within a Research Infrastructure? No Offer Description Want to explore how citizen collectives can drive societal change? Join us as a PhD in using AI-powered agent-based modeling to design adaptive
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the understanding and modelling of these processes to support robust and adaptive climate policy strategies. Your job Climate change is driven in part by complex feedback mechanisms within both natural and human
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Identifying and validating models for complex structures featuring nonlinearity remains a cutting-edge challenge in structural dynamics, with applications spanning civil structures, microelectronics
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Your Job: In the CrowdING project, you will develop agent-based movement models that realistically simulate different behaviors such as lining up, overtaking, or pushing. Based on this, you will
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a strong background in computational modeling, optimization, and systems engineering, eager to develop advanced design and simulation frameworks for battery pack topology and e-powertrain integration
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PhD: Integrated Assessment Modelling of Climate Feedbacks, Tipping Points Faculty: Faculty of Geosciences Department: Department of Sustainable Development Hours per week: 36 to 40 Application
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Main description: Native mass spectrometry is an expanding structural biology tool to elucidate the function of protein complexes. Excitingly, the demand for this technology is increasing. However
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Are you passionate about working in an interdisciplinary and international team to explore the interface between computational models, complexity science, network science, and public health