107 structures "https:" "https:" "https:" "https:" "https:" "Robert Gordon University" positions in Luxembourg
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The successful candidate will pursue doctoral research in group actions, geometric structures, and smooth dynamics under the supervision of Prof. K. Melnick, within the Department of Mathematics
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that positively impact society. For more information, please visit our website: https://wwwen.uni.lu/snt/research/finatrax/ . Successful candidates will perform the following tasks: Conduct cutting-edge research in
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Study static spin structures and compute the dynamic (time-dependent) magnetization response, where the intermediate scattering function serves as the key neutron scattering observable Contribute
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. The group consists of doctoral and post-doctoral researchers from diverse backgrounds. For more information, please visit our website: https://wwwen.uni.lu/snt/research/finatrax/projects Successful candidate
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technologies that have a positive impact on society. For further details, please visit our website: https://www.uni.lu/snt-en/research-groups/finatrax/ The candidate will support project partnerships with
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technologies that positively impact society. For more information, please visit our website: https://wwwen.uni.lu/snt/research/finatrax/projects The successful candidate will pursue a Ph.D. degree (Doctorate) in
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therapeutic target identification. GenePPS aims to overcome current limitations of perturbation modelling by integrating large-scale single-cell foundation models with structured biological knowledge encoded in
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that positively impact society. For more information, please visit our website: https://www.uni.lu/snt-en/research-groups/finatrax/
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of Europe (2016) and structured around UNESCO’s three dimensions for GCE – cognitive, social-emotional and behavioral. The successful applicant will be affiliated with the Institute for Teaching and Learning
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structure, atomic orbits, and model applicability domains Train and benchmark large-scale MLFF models on diverse molecular and materials datasets Integrate uncertainty estimates into active learning pipelines