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computational foundations of that capability and help bridge the gap between Bayes theory and practical application: knowledge integration, developing robust likelihood frameworks, sampler behavior for long
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or expected to be completed within the next six months. Experience in ecological modelling and/or Land Surface Modelling Knowledge and experience working in HPC environment. Programming experience in Fortran
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engineering, materials science/engineering or related discipline completed within the last 5 years. Solid academic and research record relevant to science and technology of cementitious materials. Knowledge
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approaches to optimize the trade-off between privacy and utility especially in the context of large models. Advance knowledge of key AI methods such as deep learning, algorithm design, probability theory
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in interdisciplinary fields, knowledge of codes in related disciplines, such as thermal hydraulics, actinide chemistry, fuel cycle analysis, particle physics, or uncertainty quantification. A minimum
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. in Quantum computing, Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a closely related discipline, with demonstrated knowledge of or research experience in
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material synthesis skills Working knowledge of common materials analysis techniques including crystallography and optical spectroscopy Demonstrated record of publishing scientific results in peer-reviewed
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),. Familiarity with data analytics, machine learning, digital twin knowledge, or Python programming language. Knowledge of additive manufacturing, process physics, thermodynamics, and/or metallurgy to interpret
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for application to nuclear, or similarly complex, thermal energy systems. Experience with open-source CFD codes such as OpenFOAM or Nek5000, and/or commercial CFD codes such as STAR-CCM+, ANSYS or COMSOL. Knowledge
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-motivated with a thirst for knowledge and a passion for performing safe work. The candidate will be expected to simultaneously execute multiple projects, contribute to development of new initiatives in