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Field
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that are only partially met by the development of special purpose classical computing units. This has motivated a recent interest in using quantum computing to machine learning tasks, in particular to clustering
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contributions to dark matter research. Collaboration members contribute to detector calibration, data acquisition, event reconstruction, background modeling, statistical data analysis, and Monte Carlo simulations
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to demonstrate skills on Data Analytics and Machine Learning, in particular on distributed ML. Must have very good programming competence in Python, Java, C/C++ or equivalent Fluent oral and written communication
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improved process understanding. Development of open-source tools for training and optimization of machine learning surrogates. Interacting with multiple faculty members within the department, as
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master degree within preferentially reservoir engineering, or within applied mathematics, computational engineering, scientific machine learning, preferably acquired recently; or who possess corresponding
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and fund availability. Responsibilities Develop advanced statistical and machine learning modeling to conduct data analyses for large-scale multimodal (genomics, omics etc) studies. Conceptualise new
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interactive system design, serious games, or real-time human-machine interfaces. Experience with AI methods such as generative models, reinforcement learning, online/adaptive learning, or uncertainty
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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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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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Details Title Postdoctoral Fellow – PKPD Modelling, Lung-on-Chip School Wyss Institute for Biologically Inspired Engineering Department/Area Position Description About the Wyss: The Wyss Institute’s