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candidate with a strong background in some aspect of numerical analysis for PDEs and an interest in scientific machine learning and probabilistic methods, who enjoys working in collaborative inter
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for an additional year. This fellowship will support an emerging scholar whose work uses interdisciplinary methods grounded in Art History to chart new pathways for the field. Area of expertise is open but should
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design scalable numerical methods for quantum master equations, implement high-performance simulations, and help build open-source tools for large-scale spin-system modeling. By improving our ability
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
and enjoy exclusive perks for numerous retail, restaurant and performing arts discounts, savings on local child care centers and special rates on select campus events. UNC-Chapel Hill offers full-time
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equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position and our department on our
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Tensorflow or Pytorch is advantageous Experience in numerical methods for partial differential equations is beneficial Effective communication skills and an interest in contributing to a highly international
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related field Strong background in numerical methods and machine learning Proficiency in at least one programming language (Python, Julia, C++, …) Good analytical skills Good organizational skills and
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and ML driven screening and optimization workflow to improve the generality of modern synthetic methods. Our first objective is to identify structural patterns and scaffolds that are accessible by
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of multi-physics and mixed-dimensional PDEs. The goal of the research is the development and analysis of computational methods combined with model order reduction methods, including data-driven ones
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NASA, Airbus, and Rolls-Royce – to develop cutting-edge, data-enhanced numerical methods that will transform how future aircraft are conceived and certified. You will work within the PinhoLab (led by