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-informed machine learning. The ideal candidate will have a strong background in developing and integrating probabilistic graphical models, Bayesian networks, causal inference, Markov random fields, hidden
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Apostolos Voulgarakis (Technical University of Crete), and the attendance in in-person international meetings and training network events. The work will mount on previous work and experience within
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such as: Advanced transportation systems modeling and simulation that could involve integrated machine learning and network equilibrium/simulation, surrogate models/ reduced order emulators or Bayesian
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. Is proficient in modern statistical modelling, AI & machine learning methods (e.g. system identification, regression models, Bayesian methods, deep learning). Is an experienced programmer in R and/or
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, and engagement with emerging technologies and societal needs in areas such as: Advanced transportation systems modeling and simulation that could involve integrated machine learning and network
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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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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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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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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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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