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systems are generally ill-conditioned. The project sits at the intersection of classical numerical analysis, scientific machine learning and computational chemistry. Based on regularization techniques and
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machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates will have the opportunity to collaborate closely
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microscopy and SEM, with computational image analysis, computer vision and machine learning. The aim is to develop robust and standardized methods to link structural, mechanical and biological properties
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changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across the network
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how AI is changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across
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, micro-CT, particle size analysis, calorimetry, and synchrotron experimental measurement techniques. Knowledge of AI-based and machine-learning methods is also beneficial. For further information about a
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University of Science and Technology (NTNU) has a vacant position as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the
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to work independently and in a team; eager to learn and to develop new (academic) skills; organized, flexible, and have attention to detail. What else do we offer you The position concerns temporary
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perform both empirical and theoretical work. You will learn how to collect and analyse data within your research area as well as communicate your results at national and international conferences and in
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information on fees. There will be a requirement to teach in undergraduate laboratories and tutorials (144 h per year) as part of the scholarship. Find out more about studying at UCD here: https://www.ucd.ie