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Field
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mesoscale fractal geometry, creating physics-informed neural network models to analyze turbulent structures, and comparing simulation results to astronomical observations to develop methods for inferring
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manipulation learning & control, and differential geometry is a plus. Knowledge of safe control methods including Lyapunov stability, barrier functions, and certified learning frameworks. Hands-on experience
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microstructural disorder, with the aim of uncovering how microstructure geometry fluctuations, heterogeneity, and collective behavior influence damage initiation and crack propagation. The position will focus
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microstructural disorder, with the aim of uncovering how microstructure geometry fluctuations, heterogeneity, and collective behavior influence damage initiation and crack propagation. The position will focus
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, geometry and analysis, with a focus on research at the interface of these areas. About the Positions Successful candidates will join a vibrant and international research environment, collaborating closely
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advance research in mathematics (algebra, geometry, and analysis). The successful candidate will engage in the construction and deepening of mathematical theories that are foundational to various areas
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geometry is a plus. Knowledge of safe control methods including Lyapunov stability, barrier functions, and certified learning frameworks. Hands-on experience with robotic manipulators (preferebly Franka
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, ergodic theory and fractal geometry Gil Kalai Combinatorics Itay Kaplan Logic, model theory David Kazhdan Representation theory Ori Gurel-Gurevich Probability, random walks, random graphs
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. Project Objectives 1. Observational studies of AGN jet geometry, collimation and acceleration: Measurements of jet shapes from parsec-scale images. Multi-year kinematics and model analysis to probe
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used to determine geometries and relative stabilities; to compute frontier energy levels, electron affinities, ionisation energies, reorganisation energies, and other descriptors linked to n‑type