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Field
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structure-preserving discretization algorithms (a refinement of finite-element analysis compatible with exact geometric, topological, and physical constraints) with artificial neural networks for achieving
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statistical analysis and coding in MATLAB/Python. The lab’s research focuses on understanding neural circuits in the descending auditory system, specifically how auditory brainstem neurons encode acoustic
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and
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real-world applications in green chemistry and industrial synthesis. Key Responsibilities: Develop and implement AI/ML models (e.g., graph neural networks, transformer-based models) for retrosynthetic
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
metabolomics data from clinical studies. Apply deep learning models (e.g., autoencoders, variational autoencoders, graph neural networks) for biomarker discovery, disease classification, and patient
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physiology and neural activity in the brain, gastrointestinal (GI) tract, and other peripheral organs. These projects have a high potential for translation towards treating a variety of neurologic and
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for action ("affordances") shape neural representations, perception, and behavior. Why this position? You will sit at the center of a uniquely cross‑disciplinary team and work closely a network of
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of neuronal loss to better understand why neurons die or axons are damaged to ultimately establish new strategies for the preservation or restoration of neural tissue. We use multiple approaches, but focus
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• Skilled in single-cell/population data analysis (e.g., GLMs, decoding) Preferred Qualifications • Background in machine learning or computational modeling (Bayesian methods, neural networks, etc