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, secure websites. Learn about updates on NSF priorities and the agency's implementation of recent executive orders . Search Menu Search search Find Funding Funding Search Award Search NSF-wide Initiatives
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include hierarchical regression models, latent factorization models, nonparametric Bayesian models, models for sequential data, mixture models, machine learning algorithms, and robustness to model
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angiogenesis 3. Applications of machine learning in cell and tissue engineering Candidates should have demonstrated publication records in cardiac and vascular engineering or biology. All positions require a
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fellow. The ideal candidate will have research experience in the economics of the auto market, especially electric vehicles. The one-year position will be under the supervision of Professor James Stock and
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, and Machine Learning. As part of an interdisciplinary research team dedicated to advancing innovation science, the fellows will apply quantitative and experimental field methods to address challenges
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Details Title Postdoctoral Fellow in Deep Learning Theory and/or Theoretical Neuroscience School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position
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(e.g., Stata, Python, or R); Creating and managing very large datasets; Machine learning skills; Designing lab experiments, field experiments, and/or surveys. Basic Qualifications A Ph.D. in operations
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Harvard community. The fellow will be required to teach one undergraduate course in modern Korean history. The fellow will have the opportunity to present their research through one of Korea Institute’s
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environments for statistical analysis (e.g., MATLAB, R, or Stata); · Creating and managing very large datasets; · Machine learning skills. Basic Qualifications A Ph.D. in any business discipline
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machine learning methods for computational materials physics and chemistry. Projects include: 1. Scientific software engineering of machine learning potentials for large scale molecular dynamics. We