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relevant to the PlanetaryBoundaries framework . Complementing this, work package 2 addresses marine biodiversity, ecosystem health, and biosphere functioning by developing and testing indicators of ecosystem
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developing and testing indicators of ecosystem resilience and systemic risk, linking biological change to Earth system stability. This position is one of several scientific positions within the project and
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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
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developing and testing indicators of ecosystem resilience and systemic risk, linking biological change to Earth system stability. This position is one of several scientific positions within the project and
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The Max-Born Institute for Nonlinear Optics and Short Pulse Spectroscopy (MBI) conducts basic research in the field of nonlinear optics and ultrafast dynamics arising from the interaction of light
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physicochemical characterization (SEM, SAXS, DLS, DSC, TGA, DMA, rheology, adhesion testing, FTIR, Raman, XPS) Quantify adhesion, cohesion, rheological, thermal, mechanical properties Establish structure–property
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, DLS, DSC, TGA, DMA, AFM, rheology, adhesion testing, FTIR, Raman, or comparable methods Evidence of scientific output (e.g., peer-reviewed publications, preprints, patents, software, industrial reports
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cell therapy products Test the function of CAR T cells in vitro and in in vivo murine disease models Requirements: We are looking for a highly motivated scientist who is enthusiastic to work in a young
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 2 months ago
-peter-lab-index.html Your tasks Building large scale foundation models Applying and further developing single cell segmentation methods Supervising a small team of PhD and MSc students Developing new
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methods Supervising a small team of PhD and MSc students Developing new foundations of augmentations for digital pathology Potentially developing multi-scale AI models for cancer patient stratification