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exascale supercomputer and world-class data facilities. This role sits at the intersection of AI at scale and HPC, giving you access to unmatched resources to prototype new ideas, run experiments, and
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Overview Our Machine Learning Research PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data
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as needs arise. These positions will support/perform a variety of complex activities in research, writing, and analysis of quantitative and/or qualitative data within the scope of research and
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Senior Policy Analyst, Duke Margolis Institute for Health Policy Hybrid (Washington DC or Durham NC)
variety of complex activities in research, writing, and analysis of quantitative and/or qualitative data within the scope of research and policy projects at Duke University. The anticipated hire will
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Senior Policy Analyst, Duke Margolis Institute for Health Policy Hybrid (Washington DC or Durham NC)
scholarship at every level. Occupational Summary Duke-Margolis is hiring a Senior Policy Analyst to join the Institute’s Biomedical Innovation research team, with a primary focus on real-world data and
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Overview At Susquehanna, quantitative researchers tackle challenging data and algorithmic problems that inform decision-making in global financial markets. Their work spans statistical inference
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well as to allow video information to be shared for both marketing, analytics and editorial purposes. By accepting optional cookies, you consent to the processing of your personal data - including
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Overview At Susquehanna, quantitative systematic traders tackle challenging data and algorithmic problems that inform decision-making in global financial markets. Their work spans signal generation
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generation, innovative clinical trial design, drug development policy, real-world data and evidence, rare diseases, and/or the use and adoption of emerging technologies such as cell and gene therapies
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Overview At Susquehanna, quantitative researchers tackle challenging data and algorithmic problems that inform decision-making in global financial markets. Their work spans statistical inference