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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
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novel diagnostic tools and treatments. Our research is truly translational: from the UT to the clinic and back. The EEG is a key clinical and research tool. EEG signal analysis includes various machine
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faces. At the same time, reinforcement learning is a key technology in artificial intelligence and machine learning that set various state-of-the-art results. In the Reinforcement Learning Lab
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-GUIDE project, we will make directed evolution guidable and, ultimately, predictable by machine learning. Specifically, you will build a first-in-class framework to expedite the design of high-affinity
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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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of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant for the new green steels compositions, including impurities and tramp elements. These models should enable
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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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algebraic geometry, or representation theory; familiarity with programming and the use of computer algebra. Our offer A position for 18 months, with an extension to a total of four years upon successful
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, ultimately, predictable by machine learning. Specifically, you will build a first-in-class framework to expedite the design of high-affinity binders that engage with therapeutic targets or efficient (bio