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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days ago
new statistical and machine learning methodology. Areas of focus include (but are not limited to): * Clustering and unsupervised learning * Dimension reduction and manifold learning * High-dimensional
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effects in Alzheimer’s Disease including manifold learning, topological data analysis, and dimension reduction techniques for biomarker estimation and causal inference methods for treatment effect
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The LIT - Leibniz Institute for Immunotherapy (foundation under civil law) (https://lit.eu/ ) – is a biomedical research centre focusing on translational immunology in the fields of cancer
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
reduction and manifold learning * High-dimensional inference and feature selection * Generative modeling and digital twins * Reliability and interpretability of ML methods The postdoctoral researcher will be
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, Lausanne 1015, Switzerland [map ] Subject Areas: • stochastic differential equations (SDEs); stochastic partial differential equations (SPDEs); stochastic processes on manifolds; multi-scale stochastic
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, Beijing 100190, China [map ] Appl Deadline: none (posted 2022/04/11 05:00 AM UnitedKingdomTime) Position Description: Apply Position Description Hua Loo-Keng Center for Mathematical Sciences (HCMS, https
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, simplicial complexes, manifold theory, fiber bundles, curvature). Familiarity with topological data analysis—persistent homology, filtrations, stability theorems—is particularly valued. Extensive experience
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Do you want to contribute to groundbreaking research in the development of a theoretical framework and numerical algorithms for evolving stochastic manifolds? This is an exciting opportunity for a
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
, geometric analysis, etc. During the first year, the position will be funded in part through the National Science Foundation Research Training Group (RTG) award: ‘Partial Differential Equations on Manifolds
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Developing models to represent structure in networks using low dimensional manifolds Modeling demographic and health trends in low-resource settings Developing a decision-making framework for policy decisions