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models, artificial intelligence, Bayesian models, data visualization, dynamic causal models, dynamic systems models, item response theory, large language models, machine learning, mixture models
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and neural network methods will be used to transfer diagnostic capability between structures in a population. Bayesian approaches will also be emphasised. The Research Associate will take a leading role
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/or semantic machine learning models and techniques, network and textual vector embedding, natural language processing, and/or advanced statistical methods for Bayesian or causal analysis Familiarity
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University of California, San Francisco | San Francisco, California | United States | about 2 months ago
– a public-private partnership conducting phase II trials of new regimens for the treatment of tuberculosis (https://www.unite4tb.org/). Application of Bayesian methods for evidence synthesis
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localise greenhouse gas emissions over large open areas enabling organisations to achieve their net-zero climate goals. Our sensor products generate large volumes of data as they scan the environment
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Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods
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& Partnerships (NSF-TIP) directorate. More information on the project is available at: https://industriesofideas.ai/ . Term-limited: This is a term-limited position for two years, with the possibility of renewal
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analysis. Nat Biotechnol 41, 604–606 (2023). https://doi.org/10.1038/s41587-023-01733-8 We Offer Excellent framework conditions: state-of-the-art equipment and opportunities for international networking
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; a global network of campuses and partners for students and faculty to leverage for learning and research; a deep investment in lifelong and experiential learning; a premium placed on pedagogical
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. This PhD will focus on uncertainty-aware machine learning models, developing and evaluating techniques (e.g., Bayesian and interval neural networks) to quantify model uncertainty and monitor it during