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the performance and scalability of large-scale molecular dynamics simulations (e.g. LAMMPS) using machine-learned potentials (e.g. MACE) through algorithmic improvements, code parallelization, performance analysis
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in soil processes, plant physiology, plant traits, and species composition Strong data analysis skills, including proficiency in R or Python coding, and/or machine learning techniques Excellent writing
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based on point defect based spin color centers in diamond and silicon carbide. Desirable: Coding skills in python for analysis of scientific data. Familiarity with infrared laser heating systems
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