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Field
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of an object or medium from measurements of waves that have propagated through it. Mathematically, such problems lead to large-scale nonlinear inverse problems governed by partial differential equations (PDEs
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to apply: Geometry & Topology (Differential Geometry, Low-Dimensional Topology, Symplectic Geometry, etc.) Partial Differential Equations (PDEs) (Linear & Nonlinear PDEs, Harmonic Analysis & PDEs, etc
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education and related services programs to assist in PennWest California’s field experience accreditation requirements. All professional development programs with field experiences leading to PDE certificates
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-month, full-time (1.0 FTE), position. The search is open to all areas of mathematics, with candidates in partial differential equations (PDE) and algebra especially encouraged to apply. Candidates should
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geometry of the space of deformations of Anosov representations, with a strong emphasis on positive ones and their relation with Geometric Analysis. Our goal is to use various techniques from geometric PDE
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differential equations (PDEs). Full-waveform inversion is a powerful approach to such problems, but its practical use is limited by the strong nonlinearity of the inverse problem and by the computational cost
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of computational fluid dynamics (CFD). Mastery of applied mathematics and numerical methods. Resolution and discretization of partial differential equations (PDEs) and the algorithm applied to the simulation
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update PDE supervisor on course progress Provide feedback on course improvements Position Status Part Time Posting Number 26FA0769 Posting Open Date 09/15/2026 Posting Close Date 10/15/2026 Qualifications
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advantageous: Semiclassical analysis Numerical analysis Spectral theory Theory of partial differential equations (PDEs) This opportunity is open to researchers within 0–5 years of PhD award, allowing for career
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new approach has emerged that integrates data and mathematical models through neural networks. This has led to the development of a method for solving partial differential equations (PDEs) known as