92 bayesian-inference-"Integreat--Norwegian-Centre-for-Knowledge-driven-Machine-Learning" Fellowship positions
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(PhD Enty Level - $108,156) p.a. plus 17% super Level B: $119,231 - $141,581 pa plus 17% super Pioneer Bayesian methods for clinical trials / Collaborate with world-class researchers / Contribute
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learning Apply for this job See advertisement About the position Integreat – Norwegian Centre for Knowledge-driven Machine Learning is seeking a motivated PhD candidate in machine learning, knowledge
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Job description: We are currently advertising for a Research Associate/Research Fellow in Causal Inference & Health Technology Assessment (HTA) to join the Health Economic and Decision Science (HEDS
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Overview The Sheffield Centre for Health and Related Research (SCHARR) are recruiting a researcher with a strong background in causal inference and interest in health technology assessment (HTA
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Postdoctoral Research Fellow in Ethics and AI Apply for this job See advertisement About the position Integreat – Norwegian Centre for Knowledge-driven Machine Learning at University of Oslo is looking for a
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Sufficient Statistics” . This position is placed at Integreat - Norwegian Centre for Knowledge-driven Machine Learning is a Centre of Excellence, funded by the Research Council of Norway. Researchers at
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for Knowledge-driven Machine Learning is a Centre of Excellence, funded by the Research Council of Norway. Researchers at Integreat develop theories, methods, models, and algorithms that integrate general and
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project “Embedded Sufficient Statistics” . This position is placed at Integreat - Norwegian Centre for Knowledge-driven Machine Learning is a Centre of Excellence, funded by the Research Council of Norway
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, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine Learning for Natural Language – Led by Prof Lexing Xie, this stream applies machine learning
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, large-grant project on the epidemiology of bovine tuberculosis in wild badgers, using state-of-the-art Bayesian modelling approaches to study the drivers of infectiousness and transmission of infection in