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. This project will develop and apply new computational/analytical tools to guide XFEL experiments for specifically tracking lattice fluctuations and ion dynamics in energy materials (batteries). The project will
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)—that is, the inability of a model to effectively process or understand visual information. This work involves integrating visual encoders with language models to create multimodal systems. The emphasis is
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powered by: Cookie Information Nettsiden bruker cookies Vi ønsker at du skal være trygg når du bruker dette nettstedet. Vi benytter cookies for å sikre at du får en best mulig brukeropplevelse og
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The doctoral student project and the duties of the doctoral student This Data Driven Life Sciences (DDLS) PhD project focuses on probabilistic models of protein structure, which can be used primarily
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for global industries, all while collaborating with experts in the prestigious International Systems Realisation Partnership. Furthermore, the student will gain invaluable skills in data analysis, problem
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analytical models, then informing a refined acoustic model taking both into account with data-driven approaches. This research is inherently multidisciplinary, lying at the interface of fluid and solid
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relevant discipline/subject area. A minimum of English language proficiency (IELTS overall minimum score of 6.5). Also, the candidate is expected to: Have excellent analytical, reporting and communication
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check our website for more information: https://www.uni-goettingen.de/de/635183.html PhD students with their own funding (e.g. DAAD) can join at any time. Tuition fees per semester in EUR None Combined
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completed scientific university education (Master's/Diploma) in food chemistry, chemistry or a related field sound knowledge and experience in the use of instrumental analytical methods such as HPLC-MS, GC-MS
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conducting experiments and performing analytical sample processing (lab work); a theoretical background in marine environmental physiology and biogeochemistry; willingness to experiment with new data