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Field
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improvements. Examples include optimizing the squeezing of the vacuum to minimize quantum noise, a prototype cryogenic interferometer, using machine learning for nonlinear feedback control, devising techniques
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
initiative to study corporate climate action and its potential to catalyze social tipping points (i.e., nonlinear shifts in societal norms, policy, technology uptake, and consumer behavior) that will
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ICFO’s Attoscience and Ultrafast Optics group works in a highly interdisciplinary field which fuses ultrafast laser physics, extreme nonlinear optics, atomic and molecular physics, SXR spectroscopy
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devices, nonlinear optics, or microwave photonics Working knowledge of simulation tools such as COMSOL or Lumerical for electro-optic modeling Desirable Skills Proficiency in Python-based data analysis
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analysis of time-frequency, ERP, connectivity, source-estimated, and nonlinear complexity features of EEG signals, as well as machine learning for neural decoding. Mentorship experience, including training
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, when dynamics are complex, nonlinear and partially unknown, such a model is typically obtained from observations by performing system identification -- one notable example is given by Gaussian process
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systems. However, when dynamics are complex, nonlinear and partially unknown, such a model is typically obtained from observations by performing system identification -- one notable example is given by
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, United States of America [map ] Subject Area: Numerical Methods for Nonlinear PDEs Appl Deadline: (posted 2025/08/27 05:00 AM UnitedKingdomTime, listed until 2026/04/03 04:59 AM UnitedKingdomTime) Position Description
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
the Principal Investigator on research in Lagrangian geometry and fully nonlinear partial differential equations, including the construction of minimal Lagrangians in complex hyperbolic space and their
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of artificial intelligence, multi-omics data integration, and functional genomics, aimed at predicting synthetic lethality in cancer - including representation learning, nonlinear embeddings, and predictive