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), combining state-of-the-art in vivo approaches with quantitative data analysis. About the lab and environment The Rebola Lab (https://therebolalab.org ) studies how variability in synaptic function across
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for the analysis of hyperspectral imaging data applied to pictorial layers, based on coupling physical radiative transfer models (two-flux and four-flux approaches) with machine learning methods. The researcher will
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, processing, visualization, interpretation…) Analyze single-cell and spatial transcriptomics datasets Decipher metabolomic patterns Perform high dimensional data analysis and integrative ‘omic’ data analysis
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fault traces visually in the remote images and topographic data and reproduces these traces as hand-drawn lines in a Geographic Information System (GIS) environment. These environments allow fault
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critical assessment of published data. Compositional analysis of stained glass windows in the laboratory by LA-ICP-MS and on site by pXRF. The latter requires the establishment of a robust calibration
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project focusing on the neural markers of stuttering, the recruited individual will be responsible for the preprocessing, processing, and analysis of data obtained from functional neuroimaging (fMRI
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, Slurm, etc.). - Strong skills in Python for data analysis and visualization. - Clear communicator with proven ability to write, synthesize, and present scientific results. Website for additional job
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experience in data preparation & analysis ● Proficiency in using Stata and/or R ● Fluency in English ● Strong intrinsic motivation to conduct world-leading, high-impact research ● Strong interest in issues
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molecular dynamics simulations of modified nucleosomes - analyze the large data set obtained using various analysis tools, from visualization to automation using machine learning tools - perform QM/MM
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combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. For more information about the total announced post-doctoral