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responsibilities for this position include the development of computational models to simulate scintillator properties using time-dependent density functional theory and Monte Carlo methods, analysis and
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, and the Center for Human-Compatible AI. We develop AI methods for applications in the health and social sciences, focusing in particular on improving health and reducing inequality. We seek applicants
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Monte Carlo methods, analysis and interpretation of data to validate theoretical models, manuscript development, and communication of research at relevant scientific meetings. The successful candidate
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EECS department, is affiliated with the Berkeley AI Research Lab, Computational Precision Health, and the Center for Human-Compatible AI. We develop AI methods for applications in the health and social
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employ state-of-the art sequencing methods to profile somatic mutations across different primate species. There is a particular focus on structural variation and employing long-read sequencing methods
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. Responsibilities: Define specific questions and methods around the effects of freshwater plume exposure on phytoplankton communities. Develop and interpret phytoplankton metrics using multi- and hyperspectral