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relationships between structure, morphology, performance (reactivity, selectivity, efficiency), and degradation mechanisms under realistic deployment conditions Participation of beam times at international large
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and optimize large-scale training and inference runs for foundation models on JUPITER (multi-GPU/node, mixed precision, parallelization, I/O optimization) Integrate multimodal data sources (e.g., scRNA
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family-friendly corporate policy Flexible working hours, the option of slightly reduced working hours ( https://go.fzj.de/near-full-time ), and 30 days of annual leave A large research campus with green
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conferences and the preparation of project reports. Develop and apply software tools. Documentations of software and data according to the FAIR data principles. Contributions to workshops and training
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reports Develop and apply software tools Document software and data according to the FAIR data principles Contribute to workshops and training activities Your Profile: Master with subsequent PhD degree in
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large multi-dimensional datasets using statistical tools such as positive matrix factorization (PMF) and cluster analysis Investigate the influence of different urban emission sectors on atmospheric
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scientific journals and conferences Your Profile: A doctoral degree in Physics, Materials Science, Computer Science, Data Science, or related fields Proven experience with large language models (LLMs), natural
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(partly) A large research campus in the countryside, which offers the best opportunities to network with colleagues and to do sports outside of work Targeted services for international employees, e.g
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using experimental data from laboratory setups Validate models through targeted measurements and structured testing procedures Analyse loss mechanisms and system efficiencies under various operating
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focus on neutron spectroscopy as main analysis technique, supported by complementary experimental techniques or theoretical simulations Hands-on participation in experiments at large scale facilities as