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to the group’s open-source software, and participation in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, computer science
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reduction, system identification, power electronics, model predictive control, multi-objective optimization, machine learning, renewable-energy integration, experimental testing, or hardware-in-the-loop
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theoretical statistics, statistical machine learning, high-dimensional inference, empirical process theory, stochastic modeling, optimization, or related areas. • Experience with writing and developing
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processing, machine learning, and human-computer interaction. The goal of this PhD is to develop neuromotor interfaces for dexterous robot teleoperation using two sensing modalities: 1) surface
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, or computer science. Core competencies: solid background in quantum many-body physics strong programming skills (Python required, Rust a plus) experience with tensor networks, variational Monte-Carlo, machine learning
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, such as statistical learning, causal inference, experimental design, probability, stochastic PDEs, algebraic statistics, normalizing flows, scientific machine learning, optimization, inverse problems
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be used to combine these datasets while accounting for their different spatial scales, uncertainties and sampling frequencies. Machine-learning methods may also be explored for retrieval, bias
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position We have a vacancy for a PhD candidate in machine learning
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of the faculty are expected to lead research programs that will produce significant contributions to a field, and teach and mentor at the undergraduate and graduate levels. This position is benefits-eligible
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Research Associate / Magma Research Fellows who have: a PhD in mathematics, computer science, or a related discipline a strong background in computational mathematics, computer algebra, or mathematical