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of inflation and phase transitions in the early universe. We are developing new data analysis methods like the use of deep learning and the use of robust statistics. This work is naturally extended to studying
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of inflation and phase transitions in the early universe. We are developing new data analysis methods like the use of deep learning and the use of robust statistics. This work is naturally extended to studying
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knowledge in statistical physics, biophysics, excellent programming skills (C++, Python,...), proficiency in spoken and written English Specific Requirements Experience with scientific modelling Experience
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Postdoctoral researcher in marine ecosystems modelling for the Marine and Continental Waters Program
Research FieldOtherEducation LevelPhD or equivalent Skills/Qualifications Required qualifications and experience Ph.D. in Marine Sciences, Marine Ecology, Statistics, Biology, or related fields applied
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of statistical packages (Stata, R or equivalent). • Experience in spatial analysis and use of Geographic Information Systems (GIS). • Ability to work with large databases and data management tools. Languages
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epidemiology and managing large databases and statistical analysis with R, Python or similar. Project management (drafting, application, execution). Fluency in English. Specific Requirements Mobility and
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to statistics (Statgraphics), and spectroscopic and chromatographic characterizations (MassLynx and LabSolutions). Reference management software. Programming in MATLAB. English and Catalan Desired: Experience in
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for the processing and analysis of multimodal spatial biology datasets. Design and apply advanced image analysis algorithms for cell segmentation, feature extraction, and debarcoding for lineage tracing. Statistically
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23 Sep 2025 Job Information Organisation/Company Universitat de Barcelona Department Genetics, Microbiology & Statistics Research Field Biological sciences Researcher Profile Recognised Researcher
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: processing and organization of microdata sets. • Statistical analysis: application of statistical methodologies to the data. • Programming (code editing): adaptation of existing scripts and code packages (in R