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Field
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, graphical models, and/or Bayesian methodologies for resolving disease heterogeneity, identifying gene-gene networks, or improving integrative genomic prediction models for common complex human diseases, with
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multiple statistical and modelling approaches, including Bayesian approaches. About the Department Ecology, Evolution, and Behavior (EEB) faculty teach undergraduate classes, advise graduate students, and
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, or network-based, Bayesian or matrix factorization methods for multi-omics integration Ability to independently perform data analysis and scientific interpretation based on omics data at an internationally
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the admission requirements for a PhD at ETH Zurich Experience in machine learning, optimization, or AI-driven decision-making Preferably with knowledge of Bayesian optimization or Gaussian processes
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questions about the position to Dr. Jessica Jaynes at jjaynes@fullerton.edu. Statistics at CSU Fullerton The statistics faculty research areas include Bayesian statistics, statistical computing, spatial
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Natural Language Processing, Applied Machine Learning, Neural Networks and Deep Learning as well as Machine Learning for AI and Data Science and Bayesian Theory and Data Analysis. We are looking
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Interview Motivated in learning new methodologies and applying new knowledge Essential Interview Knowledge of the approximate Bayesian machine learning (e.g. MCMC) (assessed at: Application form/Interview
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. Experience leading investigations linking simulations to observational data. Experience with statistical characterization of data, preferably within a Bayesian framework. Job Description: A Post-doctoral
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and reduction Development and application of big data analytics for large X-ray data sets Application of Bayesian methods to X-ray data Combinatorial analysis of various data from complementary
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health environment and 0 to 1 year of experience. Strong background in one or more areas of machine learning (Bayesian networks, neural networks, Markov Models, convolutional networks etc.) Exposure