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detailed analyses of interactions between vehicles and Vulnerable Road Users (KWGs) at roadworks. You develop and apply advanced traffic simulation models that include realistic micro-interactions. In doing
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students in 44 graduate and 56 undergraduate programs. You are encouraged to visit the university web page at http://www.uis.edu . Application deadline: 4/5/2026 Minimum Starting Salary: $16.00 per hour
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can be inhibited, leading to a form of topological delocalization. This phenomenon has never been experimentally tested. The proposed internship will contribute to the preliminary design and modeling
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to the Sustainable Built Environment (SBE). The SBE team focuses on building energy modelling and simulation, decarbonization strategies for the built environment and R&D of green building technologies such as HVAC
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subsidiarity at the territorial scale," specifically through the "materials for energy storage" program. Using molecular modeling tools, the objective is to participate in the design of a single catalyst capable
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power electronic design, modelling and simulation tools, and hardware development Knowledge of digital control implementation, testing, and characterization of power electronic components is expected
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flexibility orchestration Scalable data and machine learning pipelines Digital twin architectures for cyber-physical energy systems AI-based energy system modeling, simulation, and optimization Secure and
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, surrogate modeling of scientific processes, workflow automation and adaptive simulation pipelines, and performance analysis and optimization. The candidate will also contribute to and help originate research
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Duke University, Wuhan University and the Municipality of Kunshan, China ( https://dukekunshan.edu.cn/ ). Our campus provides an innovative and robustly interdisciplinary undergraduate liberal arts
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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 3 months ago
analysis. The goal of this thesis is to advance causal AI for wireless networks by developing statistically reliable causal inference tools grounded in recent advances in simulation-aided inference and model