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in the following areas: Deep Learning, Scientific Machine Learning, Stochastjc Gradiant Descent Method, and Numerical PDE’s - Advised by Dr. Yanzhao Cao Probabilistic Graph Theory (Network Traversal
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effects of urban greenery and develop a modelling platform to assess and optimize the cooling benefits of various types and configurations of urban greenery in Singapore Key Responsibilities • Conduct multi
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: Development, performance analysis and optimization of end-to-end science workflows, including those originating at DOE facilities. Deployment of capabilities such as AI training and inference at scale, and
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, with focus on CO, NOₓ, N₂O, and unburned NH₃. Generate modelling insights and tools to support the design and optimization of low-emission, ammonia-fueled propulsion technologies. Job Requirements: PhD
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
. The close proximity of UNC to the Research Triangle Park, which hosts numerous pharmaceutical, biotech, and healthcare companies, and to Duke University, North Carolina State University, and North Carolina
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objectives to be achieved: The work plan includes numerical modeling of the injection modeling process using commercial software, and the integration of these programs with AI-based optimization methodologies
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of numerical models (CFD) for the analysis and understanding of the behavior of the solution to be developed. Objectives:1. Designing a base design for incorporating a modular battery, 2. Develop and calibrate a
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of numerical optimization is an advantage. Experience from high-performance computing is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative
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complex properties. You will apply these models to improve tomographic image reconstruction using numerical optimization and iterative techniques. Collaboration is at the heart of the Crick’s culture. You
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learning, mathematical analysis, mathematics of data, modeling & simulation, multiscale methods, numerical analysis, optimization, ordinary and partial differential equations, numerical solvers, quantum