166 machine-learning "https:" "https:" "https:" "https:" "https:" Fellowship positions in United States
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a pioneer, harnessing state-of-the-art Omics technologies to dissect fundamental biological mechanisms, power large-scale supervised and foundational machine learning initiatives, and comprehensively
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, advertising, marketing, public relations, and broadcasting. Central has been a pioneer in extended learning for nearly 50 years, and its online programs for undergraduates and the military, as well as its
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tissue specimens Assemble analysis pipelines using machine learning to process tissue data reproducibly and at scale Conduct analyses using programming languages such as R and Python Collaborate with other
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of References Allowed Keywords statistics, biostatistics, computer science, economics, health care policy, causal inference, machine learning
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Observatory, and LSST. Expertise in modeling cosmological observables through analytical methods or numerical simulations, machine learning, statistical inference, and data reduction is beneficial. As members
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Fellowship position is available in the RSP Lab led by Dr. Sklavenitis Pistofidis. The RSP Lab (https://rsplab.org ) leverages advanced multi-omic technologies, coupled with experimental perturbations and
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/guidelines . Minimum Number of References Required Maximum Number of References Allowed Keywords statistics, biostatistics, computer science, economics, health care policy, causal inference, machine learning
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nonprofits to use machine learning and data science to modernize the public sector. We are an interdisciplinary team of data scientists, social scientists, engineers, and lawyers who are passionate about
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uses long timescale molecular dynamics (MD) simulations, integrated with experimental observables (especially cryo-electron microscopy data), and machine learning tools to better capture the dynamics
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or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented