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uptake, stress tolerance, and species interactions. A case in point is optimal partitioning theory (OPT), a dominant paradigm of plant resource allocation that describes the ability of plants to adjust
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, developing pixel detectors for high-energy physics, telescope cameras, medical imaging systems, and other scientific and industrial applications. We are seeking an outstanding candidate—creative, analytical
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expertise and approach align with these values. The successful candidate will have: a PhD in Mechanical Engineering, Computational Engineering, or a closely related discipline a strong background in
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with these molecules. A successful candidate will be familiar with the differentiation of iPSC to myeloid cells, assays evaluating viral kinetics including p24 AlphaLISA analysis and high content imaging
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approach to technical challenges. Previous experience with mouse in vivo experiments is necessary. Previous experience with neuronal activity optical imaging, particularly head-fixed imaging, is desirable
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on experimental data which you acquire. You publish the research results in scientific journals and present at international conferences You contribute to the supervision of master and PhD students At least 70% of
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | about 2 hours ago
present your findings at internal meetings and international conferences, contribute to publications, and support a positive and collegial team culture. Essential qualifications Doctoral degree (PhD) in
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of colorectal cancer (CRC) using organoid models. The researcher will focus on integrating dynamic mutations, live multiplexed transcriptomic imaging, and proteomic imaging at the cellular level to predict
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Research Associate will contribute to developing and/or applying artificial intelligence, machine learning, and image segmentation and/or data science-based methods to address cutting-edge topics, including
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progression. The Iskratsch Group , at the School of Engineering and Materials Science, Queen Mary University of London is exploiting cutting-edge mechanobiological, as well as imaging approaches2-5 with the aim