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Field
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large pan-European research initiative that brings together researchers, clinicians, and patient communities. Your project focuses on analyzing multi-omics sequencing data from thousands of patients with
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of data structures, static analyses and compiler optimizations, parallelism and concurrency) to turn these new theoretical developments into performant implementations; building state-of-the-art
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processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth observation data. Our team aims at tackling societal grand
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analysis, power analysis, mixture models, causal inference, psychometrics, sequential and time series analysis, and/or analyzing large datasets are plusses. Strong data management skills are required
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analyses using your own data and large public data resources and integrate your findings with clinical data (symptoms, EEG, etc). Finally, you will contribute to other activities of the STXBP1 team
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at the interface of data science and the scientific domains pursued at the three participating Helmholtz centers. Methodologically, a broad range of topics is covered, from large-scale data management to data mining
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on an exciting Wellcome-Trust funded project. The research focuses on decoding neural representations across dynamic brain states through advanced computational analysis of large-scale neural recordings. What you
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3 Sep 2025 Job Information Organisation/Company University of Basel Research Field Computer science » Programming Computer science » Other Mathematics » Applied mathematics Physics » Other
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keen interest in organizing large data collections and open data science are an important asset. You possess excellent collaborative and communication skills both scientifically and towards patient
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 6 days ago
of the large spectrophotometric data sets including uncertainty quantification. Combine the differently spatially and temporally sampled data sets to obtain a 4 dimensional view of organic matter products in