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Field
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first degree in Engineering or Mathematics with specialization in control systems and have completed or be about to complete a doctorate in Control Theory/Dynamical Systems or a highly relevant subject in
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created in 2017 and it is situated at the Norwegian University of Science and Technology (NTNU) in Trondheim, and the University of Oslo. PoreLab is an interdisciplinary center with joint efforts in theory
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focuses on creating new scientific knowledge for establishing new businesses and technology-driven transformation of large and small firms, as well as of entire industries. Tying together theory-driven and
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-dimensional statistics; nonparametric statistics; foundations of statistics and decision theory; applied statistics, with specific attention to large-scale applications in a wide variety of contexts
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | about 1 month ago
Description Two Postdoctoral Positions at The University of British Columbia Department: Mathematics (A) Postdoctoral research fellow in mathematical modelling and control theory in sustainable fisheries
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at the intersection of control theory and machine intelligence. Methodologies of interest include: Robot modelling, Nonlinear and Optimal control, Reinforcement learning, and Data-driven modeling and control. The Post
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to enhance our multidisciplinary research at the intersection of control theory and machine intelligence. Methodologies of interest include: Robot modelling, Nonlinear and Optimal control, Reinforcement
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of the planning and implementation processes with emerging energy technologies. You will develop and execute trainings and workshops for practitioners based on theories in Environmental psychology and empirical
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symmetries and quantum field theory, string theory and holography, amplitudes and correlators, and solitons in field theory. There is a wealth of relevant expertise, with the Group counting amongst its members
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, visualization and exploratory analysis (seasonality, etc). A strong grasp on model evaluation metrics, model evaluation and training methodologies. An understanding of probability theory and basic frequentist