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Field
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a paradigm shift in materials science by embedding mechanistic AI agents into physical experimentation cycles-enabling rapid, transparent, and reproducible design of advanced electrocatalysts. Main
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sensitive imaging and inference approaches to help guide diagnosis and treatment in cardiovascular patients. Project background Cardiovascular Magnetic Resonance (CMR) plays a central role in the non-invasive
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to understand representational drift and inter-areal communication in the brain. We use a combination of in vivo calcium imaging and Neuropixels recordings as well as computational modelling techniques
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Max Planck Institute for Heart and Lung Research, Bad Nauheim | Bad Nauheim, Hessen | Germany | about 1 month ago
Job Code: 2026_07 Job Offer from January 16, 2026 The Max Planck Institute for Heart and Lung Research (Dr. Karin Ziegler) in Bad Nauheim (near Frankfurt, Germany) invites applications for a PhD
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analyze imaging (DHM) and sequencing datasets (RNA-seq, Ribo-seq where relevant; nanopore long-read). • Perform computational analysis: differential expression, splicing, RNA processing and modification
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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | about 2 hours ago
opportunities for cutting-edge research projects. Students benefit from the extraordinary infrastructure enabling all types of cognitive neuroimaging experiments. The IMPRS CoNI covers all major imaging and
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. 124–131, Dec. 2016. [5] H. Sarieddeen, N. Saeed, T. Y. Al-Naffouri and M.-S. Alouini, “Next generation terahertz communications: A rendez-vous of sensing, imaging, and localization,” arXiv preprint
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description As a PhD student, you will be embedded in the research group Computational Imaging and
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image analysis and/or coding (e.g. Python) Exposure to TEM/cryo-EM/cryo-ET or advanced fluorescence microscopy Experience handling human-derived samples (reproductive cells/tissues) What we
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. Generative AI–based super-resolution (SR) technologies—such as VisionMetric’s iREVEAL—promise transformative gains by enhancing low-quality facial images. However, there is little scientific evidence on