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is using state of the art machine learning tools to extract interpretable latent dynamics. We seek a highly motivated PhD student to develop a predictive computational model using recurrent neural
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. This highly collaborative project, jointly investigated by PDI, TU Munich, University of Münster and HTW-Berlin, is funded by DFG within the priority programme SPP2477 "Nitrides4Future". The motivation is to
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-performance computing and imaging facilities. a collegial, international atmosphere and flexible, family-friendly working hours a structured PhD programme with extensive training and career-development
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external research funding through national and international funding agencies Active involvement in assessment and evaluation program of IFW What we offer: The research group will be supported by dedicated
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Enterprises in East Central Europe and China, 1945-1960”, funded by the German Research Foundation (DFG) within the Weave Programme. This international project, conducted in partnership with institutions in
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-analysis techniques, causal inference and quasi-experimental methods is a strong asset; Familiarity with reference management tools (e.g., Zotero, Mendeley) and systematic review tools (e.g., EPPI, Covidence
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or comparable content management systems We expect: the ability to work independently and on your own initiative a methodical and systematic approach structured and goal-oriented thinking capacity to familiarise
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research program. What will be your tasks? The successful candidate will work closely with scientists, postdoctoral researchers, and doctoral students within the department, as well as external researchers
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(TIB ) – Leibniz Information Centre for Science and Technology – Program Area D, Open Research Knowledge Graph, is looking to employ a Research Software Engineer for Ontologies and Knowledge Graphs (m/f
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master's or diploma degree in computer science or mathematics already successfully completed doctorate confident demeanor and proficient use of German and English (both equivalent to at least B2) expertise