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, artificial intelligence, network science, Bayesian methods, spatiotemporal methods, visualization, evolutionary game theory, infectious disease modeling, and assistive and accessibility technologies, with a
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such as classifier free guided diffusion models, transformers with multi-headed attention, physics-informed neural networks, materials foundational models with multi-task learning, symbolic regression
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expression systems and/or liposomes. You take an interest in liquid handling robots, Python and Bayesian optimisation. You are a team player and enjoy working in a multidisciplinary environment. You have a
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from patients with psychotic illnesses, curate and process these datasets, and derive both functional and structural brain networks. This will include using our group’s new Morphometric Inverse
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at the University of Arizona is seeking a postdoctoral research associate to develop theoretical and computational approaches for understanding how biological neural networks organize activity through nonlinear
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model classifiers (PLS-DA, random forest, neural network, etc) towards unraveling materials structure-function relationships, and are familiar with optimization approaches such as genetic search, Bayesian
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device-relevant properties Design active learning, Bayesian optimization, uncertainty-aware modeling, and other adaptive experimental design workflows to guide experiments and improve data efficiency in
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21 Sep 2026 Job Information Organisation/Company Łukasiewicz Research Network – PORT Polish Center for Technology Development Research Field Neurosciences Researcher Profile Recognised Researcher
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. Preferred Qualifications: Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other related definitions. Knowledge of federated learning SOTA algorithms. Knowledge of distributed
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an advantage: Rodent social behaviour, empathy-related behaviour, aggression, fear, or reinforcement learning tasks. Computational modelling, Bayesian statistics, reinforcement learning models, or model-based