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into commercial products that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word “challenging
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sophistication, including strong statistical skills and comfort with large-scale or complex data. Experience with computational text analysis, such as NLP methods, historical text processing, topic modeling
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to translate ground-breaking technologies into commercial products that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too
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into commercial products that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word “challenging
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the Senior Director of Labs (Dr. Ramona Pop). The position involves conducting rigorous empirical research using field experiments, large-scale data analysis, and computational methods to advance our
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the use of large administrative data to understand and address inequality. OI has published seminal work on national trends in upward mobility ; racial disparities; the role of neighborhoods, social capital
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transform visual information. We use large-scale electrophysiology and closed-loop visual experiments with macaque monkeys to discover the principles underlying cortical computation. We are seeking highly
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that is production-ready for dissemination to other laboratories and for diagnostic use, and the management of large-scale data. They will join a team of computational and experimental postdoctoral fellows
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strong command of data wrangling, cleaning, and large-scale dataset management. Machine Learning/Deep Learning: Experience with PyTorch, TensorFlow, or Hugging Face; embedding models; and model validation
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Details Title Postdoctoral Fellows, Digital, Data, and Design Institute - Climate and Sustainability Impact Lab School Harvard Business School Department/Area Position Description The Digital Data