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This PhD position is part of the WASP-WISE NEST project RAM³ – a multidisciplinary research effort at the intersection of machine learning and materials science. The project brings together PhD
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have the opportunity to contribute to a learning environment that promotes students' responsibility for their learning in a dynamic and stimulating environment in close co-operation with colleagues from
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. The applicant should have strong background in mathematical foundations of computer science and experience in Python programming. Previous experience in deep learning, reinforcement learning, or explainable AI is
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Join the cutting-edge RAM³ project: Unlocking the Potential of Recycled Aluminium through Machine Learning, High-Throughput Microanalysis, and Computational Mechanics. We are offering a PhD position
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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effort at the intersection of machine learning and applied mechanics. The focus of this position is on extracting information about what a neural network has learnt in a symbolic and (human) interpretable
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, attention to detail, and good communication skills are essential for success in this role. Flexibility and a willingness to learn are also important, as NBIS continually adapts to meet the evolving needs
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collaboration with the surrounding society in planning and implementation of education participation in the development of learning environments, teaching aids and study resources a reflective approach to student
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learning to improve predictive capabilities and efficiency in multiscale modeling. The assistant professor will be given the opportunity to develop independence as a researcher and to obtain both
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science in carrying out concrete AI projects. This includes compiling, organizing, and sharing key datasets, assisting with resource allocation proposals, conducting machine learning workflows, and