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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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has joined forces with other top universities and networks worldwide to become a truly global centre of knowledge. Within the Faculty of Science and Engineering, a 4-year PhD position is available
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that activity-silent mechanisms, such as short-term synaptic plasticity, also play an important role. We will experimentally target these two mechanisms, using EEG in combination with machine learning to reveal
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mechanics at the atomic scale. In this project, the University of Groningen will develop an array of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant
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Machine Learning Problems > Constantly questions finance/trading data and stays motivated to seek answers despite most often proving that there is no correlation or signal > Experience in setup of research
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are seeking a motivated, enthusiastic, and curious PhD candidate to join our Health Technology and Services Research (HTSR) section at the Faculty of Behavioural Management and Social Sciences. At HTSR, you'll
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Technology group led by Gabriele Keller external link . As our research group contains core members of the popular Accelerate and Stan DSLs for machine learning and scientific computing, newly developed
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, Industrial Engineering, Computer Science, or Machine Learning. Solid experience with quantitative optimization methods, including (but not limited to) mathematical programming and stochastic dynamic
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, creativity, rigor, ownership, and excitement to push research in TRL forward. Theoretical knowledge of, or experience with, machine learning such as representation and generative learning, data management, and
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of Amsterdam. Interested in developing fundamental machine learning techniques for tabular data to democratize insights from high-value structured data? Then this fully-funded 4-year PhD position starting Fall