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Computer Science at Princeton University, with the goal of developing next-generation machine-learningâ“based interatomic potentials (MLPs) for Earth and planetary materials across extreme pressureâ“temperature
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stakeholders involved in planning and decision-making. Qualifications Candidates must have a PhD in atmospheric physics, hydrology, meteorology, Earth system science, climate studies, applied mathematics
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to lead an investigation exploring the ability of recently developed global earth system models to simulate coastal sea level across sub-annual timescales. This work will leverage a suite of coupled models
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