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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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, concentration and functional inequalities • Mathematical aspects of machine learning and deep neural networks • Free Probability aspects of Quantum Information Theory. While excellent candidates with other
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extension. Your Tasks Our overarching goal is to understand the neural mechanisms of cognitive functions, focusing on learning, attention and decision making. We investigate the contribution of subcortical
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date. Proven expertise in AI/ML/DL techniques for generative or analytical purposes (e.g., generative adversarial networks, convolutional neural networks, diffusion models, or other emerging methods
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for generative or analytical purposes (e.g., generative adversarial networks, convolutional neural networks, diffusion models, or other emerging methods), with evidence of application in research or professional
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. The appointment is for one year, renewable for a second year given the availability of funds. The focus is on fundamental properties of simulated neural networks, like neural scaling laws, as they manifest in
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learning architectures including generative models, particularly for sequence or structural data (e.g. transformers, graph neural networks) Proved experience in working independently and as part of a
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intelligence, including reinforcement learning, computer vision, and deep neural networks applied to robotics. Track record of peer-reviewed publications and active participation in interdisciplinary research
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of this position will be development of custom neural networks for functional annotation of protein sequences. This is an Extended Temporary Employment (ETE) position. Outstanding UA benefits include health, dental
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modelling and simulation of complex systems reinforcement learning or graph neural networks proficiency in Python and related computational toolchains a strong interest in interdisciplinary research bridging