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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | about 6 hours ago
: preparation and analysis of biological samples for mass spectrometry calibration and quality control of the mass spectrometer analysis and interpretation of proteomics data collaboration with computational
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networks and flow fields in porous materials Evaluation of large tomographic data sets as input for mechanistic and AI-based reactive transport models Presentation and publication of original scientific
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | about 6 hours ago
and cleaning Routine sample measurements and data analyses (e.g. protein identification and quantification, determination of Mw) Acquisition, evaluation and analysis of LC-MS data in scientific projects
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cells of individuals at high risk of developing type 2 diabetes and its complications. Tasks Perform end-to-end data analysis, including quality control, data integration, and inference of regulatory
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multi-omics data resources to drive innovative research REQUIREMENTS: Master’s degree (or higher) in (bio-)statistics, epidemiology, mathematics, or a related discipline Proven proficiency in R Solid
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focus here is on the transparent detection of erroneous or corrupted measurements using artificial intelligence. Current XAI approaches can provide relevant additional information (e.g. feature importance
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degree programmes must have a designated STEM focus. It must be a tuition-free Master's degree programme. Please read point A.15 in the important information for scholarship applicants. Funding is not
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the following additional benefits for uninterrupted stays of over 6 months in Germany after start of funding: monthly rent subsidy (please read the important scholarship information / section F, point 9) monthly
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covered by other funding providers: Further information Further information For further information see: www.daad.de/dlr Application requirements What requirements must be met? At the time of
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications