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theory & experiment: Co‑design validation experiments with experimentalists; iterate models using feedback from new measurements. Automate the workflow: Build Python workflows for simulation and data
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templates for distributed AI training, agentic AI with modeling and simulation, and end-to-end workflow monitoring, profiling, and optimization. Working with quantum simulation tools, including NVIDIA CUDA-Q
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, or a related numerical field. Programming experience in one or more of: Python, C++, Fortran, Julia. Hands-on experience building and training AI models with frameworks such as TensorFlow or PyTorch
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communication skills. Desired Qualifications: Experience with fitting parametric models to neural population data. Experience with high-performance computing. Notes: This is a full-time, 2 years, postdoctoral
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, machine learning or AI to computational modeling, simulations, and advanced data analytics for scientific discovery in materials science, biology, astronomy, environmental science, energy, particle physics