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23.10.2025, Wissenschaftliches Personal Automated cell culture systems are transforming the way we study complex biological processes. By enabling reproducible, standardized, and high-throughput
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methods, signal processing techniques, and data analysis pipelines for novel X-ray imaging modalities, including ghost imaging, quantum-enhanced imaging, and other correlation-based methods. As part of a
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Novel Broadband (Visible-to-Shortwave Infrared) CMOS Image Sensor Pixel Architectures Job description The Image Sensor Group in the EIectronic Instrumentation Lab is looking for a postdoctoral
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regenerative medicine in the lab of Dr. Kai Mesa at Princeton University. The Mesa Lab has pioneered innovative intravital multiphoton imaging techniques, paired with advanced mouse genetic tools, to observe and
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. This work covers three main areas: Data Rescue – enhancing the joint WMO–C3S data rescue portal, developing a prototype image repository, improving the Data Deposition Service, and developing innovative
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intelligence-based automated interpretation of medical images, and new knowledge on the human visual system into the screening mammography reading process. Combining these new capabilities and new knowledge has
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to the project, uniting experts in battery technology and acoustic signal processing and machine learning. The goal is to harness advanced data science techniques to establish a novel paradigm for online non
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tracers. Specifically, you will use clinical molecular imaging data in combination with numerous methods (i.e., AI image analyses, PBPK modeling, immunohistochemistry, FACS). As a postdoctoral researcher
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, proficiency in standard molecular biology and biochemical techniques, experience with 3D image processing and modeling software for structural analysis (such as IMOD and UCSF Chimera). A strong background in
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large animal models, lymphatic research, and MRI. The scholar will be supported by MR technologists (MRI studies), plastic surgeons (lymphatic surgery), radiologists (MRI studies and imaging evaluation