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. Within this project, work package 1 focuses on the resilience of the marine sinks of heat and carbon, using Earth system and biogeochemical models, observational data, and scenario analysis to identify
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computational methods for analysis and interpretation of large-scale biological datasets. Experiences in structural homology modelling is not essential but would be advantageous. The post holder will work in a
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extensive use of surface science methods and also includes the most advanced methods of microscopy through its collaboration with VISION. Visiting large scale facilities such as synchrotrons for EXAFS and
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-of-the-art, large-scale discrete/combinatorial problems. Detailed information about the group can be found on the PCOG website . Your profile Required qualifications and experience: PhD in any discipline
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. Further information can be accessed by visiting our webpage at www.csbdresden.de Fellows have full access to state-of-the-art research facilities and infrastructure on the campus. Dresden is a vivid and
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum
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(e.g. R, Python) and an ability to work with large datasets Strong record of peer-reviewed publications Ability to independently design and execute experiments and interpret data Ability to work in a
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econometrics The candidate should show some acquaintance in managing large datasets and non-traditional data, e.g. GIS, satellite-based, social media Fluency in English; a good understanding of French will be
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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Job description: At the University of Vienna more than 11,000 personalities work together towards answering the big questions of the future. Around 7,700 of them do research and teaching, around