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structural models and compute electronic and vibrational properties. Develop and train neural-network or other machine-learned interatomic potentials to enable large-scale molecular dynamics (MD) simulations
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application of ultrafast THz-pump and optical-probe techniques to detect narrow-band THz radiation and explore mode-selective dynamics in quantum and molecular systems. This work leverages state-of-the-art
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developing LLM-based applications using Python APIs. Experience with large scale molecular dynamics (MD) packages e.g. lammps Experience with version control (e.g., Git) and collaborative software development
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to the Lab’s broader effort in CH4 and CO2 utilization R&D. The role will require the individual to work with personnel that perform machine learning and molecular simulations and electrochemical device testing
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contributions in: Building novel generative models for predicting genome-scale evolutionary patterns using GenSLMs Developing scalable models that can, when integrated with high throughput molecular dynamics
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of molecular reactions occurring at the surface of various materials. In addition, computational fluid dynamics (CFD) simulations combined with microkinetic modeling will be carried out to study the heat