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analysis, algorithm development, simulation, and hardware-in-the-loop experimentation. The Research Fellow will work closely with the Principal Investigator and collaborators/students across NTU Singapore
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-Informed Neural Networks (PINNs) and hybrid models that respect the physical laws governing the real-world system Applying Deep Reinforcement Learning (DRL) algorithms to optimize processes within simulation
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dynamic thermal simulation of buildings with standard lightweight façades. Development of an innovative numerical model in EnergyPlus that allows for the simulation of buildings with dynamic thermal
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43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. ... (Video unable to load from YouTube. Accept cookie and
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· Lead the design and implementation of mixture-of-experts neural architectures and reinforcement learning pipelines for counterfactual disease trajectory simulation for EMED, an NIH-funded multi-modal AI
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simulations and future climate scenarios, knowledge of climate change detection and attribution methods and relevant experience with scientific academic writing. Further particulars are included in the job
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TT Electronics, Transformers and Rectifiers, Siemens, and NEMA, contributing across the full project lifecycle from requirements capture and simulation through to system integration, test and reporting
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and Management within R&D Projects, by the Code of Administrative Procedure (CPA), all in their current wording, and by other applicable national and community legislation. Procedure Reference: IT1375
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frequency high temperature operation of Wide Band Gap (WBG) SiC Semiconductor devices and applications. (2) Establish foundational work in the modelling, design, performance evaluation, and benchmarking
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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 internal