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At the University of Vienna almost 11,000 personalities work together towards answering the big questions of the future. Around 7,700 of them do research and teaching, around 3,000 work in
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(45%) • Support statistical analyses of large data sets from an epidemiological cohort, investigating associations with birth outcomes using both targeted and nontargeted data (25%) • Support
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18 Sep 2026 Job Information Organisation/Company KTH Royal Institute of Technology Research Field Computer science » Other Economics » Other Engineering » Control engineering Engineering » Systems
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-performance computing, particularly in the theory of efficient string and data structures, sequence indexing, and large-scale data analysis. Experience with the Burrows–Wheeler transform, pattern matching, and
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systems, or large-scale data pipelines. Evidence of open-source software development, reproducible research practices, and successful interdisciplinary collaboration. Demonstrated record of scholarly
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work independently as well as in a team. Experience in large-scale research project management and development, knowledge of statistics and big data analysis would be highly desirable. The appointee will
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bioinformatics and spatial analysis techniques to large-scale spatial transcriptomics and imaging datasets, using tools such as MuSpAn to identify spatial biomarkers and uncover the biological mechanisms driving
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information and data through observation, experimentation and various other methods, to include operating highly technical laboratory instruments and equipment. -Analyze sequencing data from large sample sets
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at the Large Hadron Collider (LHC). The successful candidate will contribute to a broad research program that includes physics analysis, detector performance studies, experiment operations, and upgrade
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 18 days ago
. Description: Under the guidance of a mentor, the participant will engage in a NASA-aligned research project advancing data-driven approaches to characterize wildfire risk and post-fire vegetation recovery