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expertise in fields that are of great important for the Tenure Track position, such as Machine Learning, Neural Networks, Optimization, Applied Harmonic Analysis, Inverse Problems, Quantum Information, and
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developing novel mathematical methods with applications to data science and artificial intelligence. The position serves as a pivotal connection between the Faculty of Mathematics and the Research Network
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recognition, brain-inspired or spiking neural network approaches, predicting material properties, optimizing processing parameters for next-generation energy technologies, analysis of "big data" generated from
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interdisciplinary areas. Research fields of particular interest include, but not limited to: biomedical science and engineering veterinary science computer science and data science neuroscience and neural
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across these 3 research lines is to adopt fit-for-purpose and holistic solutions, which typically involve data-driven AI approaches, relying on neural networks, reinforcement learning, graph neural
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Professor, within the Cognitive and Behavioral Neuroscience program in the Psychology department, will have expertise at the intersection of Artificial Intelligence (AI) (e.g., deep neural networks and large
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as an innovative and dynamic institution. We were one of the first higher education institutions to hire a Chief Artificial Intelligence Officer (https://www.gmu.edu/AI). Departmentally, we have
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trustworthy AI architectures in domains such as generative AI, large language models, neural networks, and imaging as well as to integrate various types of data to advance research and improve clinical decision
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following areas: Probabilistic or Bayesian Machine Learning Variational Inference, Ensemble, or Diffusion Models Spatio-Temporal or Sequential Modelling Graph Neural Networks Deep Learning and Uncertainty
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consider strong candidates in any research area but will prioritize Artificial Neural Networks. A PhD in computer science or a related area is required. The successful candidate will receive a competitive