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multidisciplinary team and use state of the art methods such as Nanoindentation, Raman Spectroscopy, Digital Light Processing, Two-Photon Lithography, Electron Microscopy, and Numerical Simulations. Your research
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on methods development in machine learning, uncertainty quantification and high performance computing with context of applications from the natural sciences, engineering and beyond. It is embedded in
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lung and bladder barrier models (membrane-based organ-on-chip models) and for exposing those to bacteria and potential target drug compounds. A variety of analysis methods (fluorescence microscopy, mass
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also be opportunities to contribute to numerical simulations and formal asymptotic analysis. The project will involve tools from: Spectral theory and functional analysis, Dynamical systems and modulation
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are seeking a Research Fellow to contribute to a project focused on Numerical Methods for McKean-Vlasov PDEs. Key Responsibilities: Develop Numerical Methods for McKean-Vlasov PDEs/Master equations Job
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, or a closely related field. Preferred Qualifications Demonstrated experience in continuum mechanics or statistical mechanics. Expertise in developing custom numerical solvers or using advanced
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, particularly in the context of wave equations. Proficiency in numerical implementation and computational methods will be appreciated. Candidates with a PhD in semiclassical analysis who are keenly interested in
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impacts on natural resources, urbanizing land use and agriculture and developing mitigation and adaptation strategies. In addition to regular courses on fluids and numerical methods, candidate is expected
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. Demonstrate sufficient breadth and depth of specialist knowledge in the discipline and of research methods and techniques to work within established research programmes. Show a proven ability to communicate
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care for eligible 5-year survivors of childhood cancer treated at St. Jude Children's Research Hospital. In addition, the clinic supports numerous research initiatives focused on characterizing and