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and to acquire valuable research experience. The PhD Project Life in the Greek-speaking cities of the Eastern half of the Roman Empire was infused with cultural interactions and the rich and pluralistic
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chemistry or a related field. Very strong academic performance. Experience in molecular machine learning. Experience with the programming language Python. Experience in computational chemistry. Basic
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that can be used for training machine learning and deep learning models. You will work in tight collaboration with other researchers in Nijmegen, Delft and at the Hubrecht Institute (van Oudenaarden group
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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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for this position will have the following qualifications/qualities An MSc degree in chemistry or a related field. Very strong academic performance. Experience in molecular machine learning. Experience with
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that would give you an advantage) Experience in computational modelling (e.g., agent-based Bayesian models, cognitive learning models, machine learning, robotics). Experience in annotation software such as
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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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Research Group Twente: The research focus of the statistics group is on the development of statistical methodology for new data applications and the theoretical analysis of machine learning methods, in
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. Research methods include computational modelling, brain imaging (fMRI), machine learning, behavioural methods, and other techniques. Virtually everything we sense, think and do is uncertain. For instance
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High