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— Plasma diagnostics and experimental data analysis â— Plasma control and instability prediction â— Signal processing and data-driven analysis of plasma measurements Requirements: â
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to validate predictions made by their machine-learning models and drive wet-lab discoveries. The candidate may also have opportunities to work with research software engineers to translate their research
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spectrometric datasets. A major focus will be on the application of AI/machine learning models and other computational methods to discover unknown metabolites that have strong associations to experimental
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model biases, and identify sources of predictability. The project will involve; 1) rigorous interrogation of NOAA GFDL's CM4X simulation output with respect to coastal sea level variability and relevant
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science and engineering applied to stakeholder-relevant issues. The scientists will collaborate with Princeton and NOAA/GFDL researchers to expand the reach of GFDL's model data (both historical and future
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-year appointments. Salary and benefits are competitive and commensurate with experience, following Princeton University guidelines. Research Scope Benchmarking and evaluating existing foundation models
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positions. Dr. Wei Peng's group (www.weipengenergy.com) focuses on modeling institutional and human dimensions of energy transition to identify realistic and robust decarbonization strategies. The appointment
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science. The postdoc will work on a variety of projects, which may include methods for large language models, the impact of artificial intelligence on society, as well as broader questions surrounding
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., Datavyu), longitudinal data analysis (e.g., RI-CLPM, growth-curve analysis), multi-level modeling, and experimental study design. Expertise designing studies with parents, infants, and school-aged children
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Science and Engineering Dynamics and Controls Systems Energy and Climate Fluid Mechanics Lasers and Applied Physics Materials and Mechanical Systems Robotics. This position is not eligible for sponsorship