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Field
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Carilion (VTC). About the Lab: The lab integrates state-of-the-art neural recording technologies, complex cognitive tasks, and computational models to investigate the neural basis of flexible cognition. From
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determines observables of the replication program such as the Mean Replication Timing (MRT) and the Replication Fork Directionality (RFD) profiles. We proposed a strategy to train a neural network to infer
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by connectome-constrained artificial neural networks. Candidates from outside the field of neuroscience are encouraged to apply, but must be curious, persistent, and passionate to delve
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. Key Responsibilities Research & Development: Integrate Physics-Informed Neural Networks or Reinforcement Learning to create realistic human movement and interactive social behaviors within XR
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include coastal features such as seagrass meadows, salt marshes, and dunes, and their dynamic interactions with waves, currents, and sediment transport processes. Artificial Neural Networks for coastal
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highly collaborative research team dedicated to advancing our understanding of epilepsy, sleep physiology, and neural networks through cutting-edge clinical and translational research. Working alongside
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frameworks. L–H/H–L transition physics, pedestal evolution, or core-edge coupling. Analysis and validation using experimental data from tokamak facilities. Machine learning, scientific AI, neural-network
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such as transformers, self-supervised learning, multimodal learning, generative models, graph neural networks, or foundation models. Experience with structural and/or functional brain modeling. Familiarity
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Qualifications Experience with graph neural networks, machine-learning interatomic potentials, or related scientific machine-learning methods for atomistic systems. Familiarity with uncertainty quantification
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human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and five centers and institutes that focus