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of their mental models into a machine learning model, using dynamic Bayesian networks to understand, propagate and reduce uncertainty in their assessments. The research will apply models of distributed situation
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Join an international MSCA network and help advance
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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 innovation
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significant external research funding. Experience supervising doctoral or postdoctoral researchers. Expertise in Bayesian and/or adaptive trial designs and dose-finding methodologies. Strong leadership and team
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like LiteBIRD and FOSSIL. We have a large international network of collaborators, and as a doctoral fellow you will have many opportunities to travel and collaborate with researchers at other
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Trials Research Network (CTN+) is offering a 6-month Research Assistant 2 position in research methodology based at McGill University. The position focuses on developing advanced methodology to evaluate
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radio interferometry data, particularly very long baseline interferometry. Experience with or skills relevant to statistical modelling and Bayesian inference. Demonstrated familiarity with the fields of X
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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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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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candidates with strong expertise in Bayesian methods, uncertainty quantification, and/or machine learning applied to nuclear theory. The group’s research spans a wide range of topics including nuclear