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Field
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implications for climate risk assessment and societal resilience. The team uses integrated observations, reanalysis datasets, climate model simulations, artificial intelligence, and statistical approaches across
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, converter control, and energy systems. Design, model, simulate, and develop advanced power electronic converter topologies and associated control algorithms. Investigate high-efficiency and high-power-density
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modelling and advanced cooling at high temperature of SiC devices. (6) Simulation model of new SiC devices (7) Loss modelling and analysis (8) EMI filter design (9) Gate driver design (high frequency and WBG
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(Lua/Java), agent behavior modeling, event handling, and API-based integration with external AI systems. Experience with distributed systems, reinforcement learning, or simulation environments (e.g
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modelling and advanced cooling at high temperature of SiC devices. (6) Simulation model of new SiC devices (7) Loss modelling and analysis (8) EMI filter design (9) Gate driver design (high frequency and WBG
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complete application consists of: An application Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from
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-driven surrogate models for real-time reconstruction and forward simulations. Create numerical algorithms for physics reconstruction using sparse data. Implement assimilation pipelines which integrate
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network from high-impact, low-probability crisis events. This project addresses critical challenges in dynamic modelling, DT federation, and decision support to help stakeholders manage crises ranging from
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, and modeling tools (e.g., Python, MATLAB, TCAD, photonic simulation software). Strong analytical, problem-solving, communication, and teamwork skills, with the ability to work independently in a
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Oden Institute for Computational Engineering and Sciences | Austin, Texas | United States | 2 months ago
hemodynamics AI-integrated computational simulation (“digital twins”) Translation of computational methods into clinical cardiovascular practice Advancing precision cardiology through mechanistic modeling