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applied mathematics, physics, computer sciences or social sciences with outstanding skills in quantitative methods ; - Provable experience working with social media data, specially very large datasets (we
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of propagations of high-energy particles through magnetized medium and analysis of data of different gamma-ray telescopes: Fermi Large Area Telescope, Cherenkov Telescope Array Observatory (CTAO), Large High
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their effects on large-scale-structure (LSS) statistics as measured by the power spectrum and bispectrum of galaxies or intensity maps. The project emphasizes spectroscopic galaxy surveys—in particular
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for analysis of large-scale bulk and single cell data sets Strong understanding of statistical modelling, data normalisation and machine learning methods applied to biological datasets Experience with data
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programming and scripting (e.g. R, Python, Bash) for data processing, integration and visualisation Proven experience developing and using necessary pipelines for analysis of large-scale bulk and single cell
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Modelling (MLM), and latent profile analysis. Experience in managing projects, implementing large-scale surveys, and analysing large datasets are relevant strengths. The appointee should also have a high
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to evaluate disequilibrium in trait–environment relationships across time and space. Analyze trait, fossil, and environmental datasets to assess climate tracking and climate fidelity. Collaborate with a large
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connected large wind energy system dynamic modelling, control and analysis. In particular, the objective of this research programme is to lay the foundations of a new, model and methodology for Advanced wind
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at CRAG (from basic science to applied research using plant experimental model systems, crops and farm animals) make extensive use of genomic technologies and large sets of genetic and genomic data (https
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on emergency medicine health services, care transitions, and population-level outcomes. Utilize advanced quantitative methods to analyze large healthcare datasets, including Medicare and Medicaid claims (MedPAR