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large language models in distributed environments while safeguarding both model integrity and data confidentiality. The successful candidate will develop novel frameworks that enable effective
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in AI, bioinformatics, statistics, computer science, data science, machine learning, epidemiology, or related fields with a relevant PhD degree (required). Experience with analyzing large genetic data
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The Bhatt-Duchene Group is based in the Section for Health Data Science and AI at the University of Copenhagen's Department of Public Health. The group works at the intersection of computer science
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crystallographic and scattering data analysis, including handling large datasets. Solid understanding of crystallography, powder X ray diffraction, diffuse scattering, phase transitions, and background modeling
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Understand and analyse data from large scale DTU pilots Conduct pilot-scale CO2 capture experiments up to TRL7 Travel to secondments at the University of Leeds in the UK, Institut for Energiteknikk (IFE) in
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Microeconometric methods Empirical research based on administrative and register data Profile 2: Macroeconomics and Macroeconomic Modelling Macroeconomic theory, including competing paradigms and approaches
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work environment spanning from biochemistry to marine ecology with a strong focus on experimental and hypothesis driven work. Importantly, a large part of the work will happen in close collaboration with
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, teaching, and outreach activities in international business to enable students, companies, and society at large to address the grand challenges in a highly volatile and unpredictable world. The successful
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the section, and the wider department hosts a large and vibrant community of young researchers, some of whom work on related topics and/or use similar methods. We are located on Frederiksberg in Copenhagen
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Experience with synchrotron X ray scattering and/or XFEL experiments. Strong skills in crystallographic and scattering data analysis, including handling large datasets. Solid understanding of crystallography