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computational mechanics and numerical modeling methods such as finite element analysis (FEA) and multi-body dynamics for hydro-mechanical drilling systems Proficient in structural dynamics modeling and system
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proposals. Strong background in advanced Fourier analysis, statistics, numerical linear algebra, optimization, tensor analysis, machine learning, and generative modeling. Established expertise on iterative
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) in the Research Group “Numerical Mathematics and Scientific ComputingNumerical Mathematics and Scientific Computing“ (Head: Prof. Dr. V. John) starting as soon as possible. The work tasks include
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techniques. The ideal candidate will have prior exposure to modern developments in at least one of these fields: Optimal Transport, numerical analysis of PDEs, functional analysis, mathematical foundations
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prior exposure to modern developments in at least one of these fields: functional analysis, numerical analysis of PDEs, mathematical foundations of deep learning, optimization, approximation theory
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• Analyse data and generate insightful reports to inform decision-making. • Streamline processes and systems to optimize efficiency and enhance the stakeholder experience. • Contribute to ad-hoc
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access to state-of-the-art numerical models and high-performance computing systems at Princeton and in NOAA, working alongside GFDL model developers and software engineers to advance quality assurance and
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Recommendation Systems Wukong: Towards a Scaling Law for Large-Scale Recommendation FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference ML numerics, pruning, distillation, and optimizer
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receives the care he or she deserves to achieve optimal outcomes. The research endeavors by faculty and investigators in the Section of General Surgery are just as wide and varied as the diseases they treat
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digital twins to develop innovative solutions for monitoring, analyzing, and optimizing urban systems in real time. The candidate will contribute to modeling interactions between physical and digital