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of future reactor systems with a focus on systems relevant for Norway. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations
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processes of the study systems of our collaborators. Core components of the research involve, among others, Bayesian hierarchical modelling, shrinkage methods, machine learning (ML) or dimension reduction
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needed, and otherwise contribute to overall lab operations. The applicant will be a collaborative, impact-focused problem solver who wants to be part of a dynamic team. Learn more about the innovative work
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to high-performance computing facilities and datasets from laboratory experiments will be provided to support simulation and verification of the resulting model. Replicate and learn a theoretical model for
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metal dichalcogenides are promising platforms for next-generation quantum and electronic devices, where atomic defects play a crucial role in determining functionality. This project develops a machine
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projects, as well as in multiagent systems, including computational game theory, security games, machine learning in multiagent settings, automated planning under uncertainty, social networks and others
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focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute
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. The project is supervised by Associate Professor Ulysse Côté-Allard at the Department of Technology Systems, University of Oslo, whose research focuses on the development of machine learning algorithms
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engineered constructs. Learn more about the innovative work led by Dr. Chris Chen here: https://bdc.bu.edu/bdc-team/. What you’ll do: Independently conduct research on liver cell proliferation, expansion, and
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, or comparable research experience, along with significant experience in machine learning, computer programming, computational biological applications. A strong background in statistics and biology. Experience