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will use the suite of machine learning tools that is readily available in Python packages. In other words, we will not focus on the development of new machine learning tools as everything we need is
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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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, 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
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inventory, a major incentive for the project is the application and adaptation of state-of-the art machine learning codes to deal with redshift distortions, intrinsic (galaxy) biases, survey selection biases
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of political violence: from the role and effectiveness of sanctions during military disputes to the increasing importance of non-state actors in war, and from the effect of non-governmental organizations
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adaptation of state-of-the art machine learning codes to deal with redshift distortions, intrinsic (galaxy) biases, survey selection biases and in particular the complications encountered in photometric
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description A wealth of academic research has recently tackled new dimensions and aspects of political violence: from the role and effectiveness of sanctions during military disputes to the increasing
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evolution guidable and, 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