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quantification, and rigorous methods for differential equations and scientific machine learning; geometric deep learning, manifold learning, equivariant methods, high-dimensional geometry, and
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quantification, and rigorous methods for differential equations and scientific machine learning; geometric deep learning, manifold learning, equivariant methods, high-dimensional geometry, and
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to work with Professor Elena Beretta on inverse problems for nonlinear partial differential equations arising in the life sciences and medical imaging. The successful applicant will contribute to a
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scientific supervisor, support activities related to the development, implementation, and validation of computational methods for problems described by partial differential equations and finite
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Mathjobs.org | 29 days ago
learning, inverse problems, uncertainty quantification, and rigorous methods for differential equations and scientific machine learning; geometric deep learning, manifold learning, equivariant methods
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learning, inverse problems, uncertainty quantification, and rigorous methods for differential equations and scientific machine learning; geometric deep learning, manifold learning, equivariant methods
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methods for increasingly large and complex systems of coupled nonlinear delay-differential equations (DDEs). Models range from arrays of single-mode semiconductor lasers described by Lang–Kobayashi-type
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use a variety of mathematical and computational approaches-including optimal transport, gradient flows, partial and ordinary differential equations (PDEs/ODEs), and cell-based simulations-to develop
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, Partial Differential Equations, Functional Analysis, Mathematical Physics, Algebraic Topology, Algebraic Geometry and Algebraic Number Theory, Combinatorics and Algorithms, Category Theory, Logic and its
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of Partial Differential Equations. The opening is for academic year 2027-2028. We are interested in candidates who will contribute to mentoring through teaching, research, and service. The initial