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learning, or related quantitative field. • Proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods. • Strong interest in
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deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods. • Strong interest in interpretable ML and mechanistic model discovery. Submit a
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on the topic of materials, and numerical modeling. Research will be conducted on infrastructure materials and urban heat modeling. The successful candidate will contribute to an ongoing effort on
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by two NIDA-funded grants. The first project, NEURONIC, utilizes a nasal spray paradigm to assess reactions to nicotine in a controlled, laboratory setting as a model of risk for addiction