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generating functions, and discovered algebraic P-fields, initiating an algebraic-geometric construction of A-model Landau–Ginzburg string theory. His recent interests include the mathematical formulation
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analysis of the ATLAS experiment data. The L2IT team plays a driving role within the ATLAS collaboration for the reconstruction of charged particle tracks using geometric deep learning (GDL). The person who
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activities through collaborative service work. Qualifications: Doctoral Degree in mathematics with specialization in model theory or related area required. Research interest in geometric stability and
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reconstructions of urban and industrial environments. The second axis of work will develop visual change detection – both at on object-level and geometric-level - using Visual Language Models such as CLIP, DINOv3
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Probability, Gaussian processes, discrete probability, extremal combinatorics Zlil Sela Geometric group theory, model theory Alexander Sodin Mathematical physics, spectral theory Evgeny Strahov Random
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systems, and how material, geometric, or multiphysical disorder controls emergent mechanical behavior. The postdoctoral associate will have substantial independence in developing theoretical, computational
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with Prof. Mauro Maggioni on problems that include: analysis and algorithms on graphs, geometric analysis of high dimensional data sets, dynamic data sets, scientific machine learning, high-dimensional
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Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid
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to ongoing work by Dr. Megha Khosla on trustworthy graph machine learning, especially on the relationship between transparency and privacy in graph-based models. Population-scale network data are highly
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applications. This includes, but is not limited to, stochastic differential equations, stochastic partial differential equations, variational and geometric methods, probabilistic numeric, optimal transport, and