Develop machine learning algorithms and neural networks for modeling and/or accelerating PDE simulations; Perform uncertainty quantification on machine learning models for PDEs; Utilize supercomputing resources for PDE and machine-learning models; Perform data analytics on large-scale datasets; Work in a multidisciplinary team environment including mathematicians, computer/computational scientists, and domain scientists; Author peer-reviewed journal articles and contribute to research proposals
Requirements:
Ph.D. in Applied Mathematics, Computer Science, or the Physical Sciences/Engineering within the last 3 years, with a strong research background in applied mathematics, machine learning, and scientific computing; Demonstrated research experience in development of physics informed machine learning; Keen interest in extending mathematical and scientific computing techniques to new problems
Text:
Machine Learning Postdoctoral Researcher Develop machine learning algorithms and neural networks for modeling and/or accelerating PDE simulations; Perform uncertainty quantification on machine learning models for PDEs; Utilize supercomputing resources for PDE and machine-learning models; Perform data analytics on large-scale datasets; Work in a multidisciplinary team environment including mathematicians, computer/computational scientists, and domain scientists; Author peer-reviewed journal articles and contribute to research proposals Ph.D. in Applied Mathematics, Computer Science, or the Physical Sciences/Engineering within the last 3 years, with a strong research background in applied mathematics, machine learning, and scientific computing; Demonstrated research experience in development of physics informed machine learning; Keen interest in extending mathematical and scientific computing techniques to new problems
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