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for its expertise in correlative imaging and materials science. To advance our microplastics research, we are looking for a highly motivated Postdoctoral Researcher with strong expertise in fluorescence
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the field of hyperspectral fluorescence imaging and detailed optical spectroscopy of the interaction of carbon nanotubes with chiral molecules adsorbed on or encapsulated within the SWCNTs. Position You will
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) detection, we will make AI for medical imaging transparent, robust and data-efficient. Position Overview As a postdoctoral researcher, you will forge next-generation explainable medical foundation models. You
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image sequences. As a benchmark, end-to-end deep learning models will be developed using raw image data. In parallel, shallow learning models (e.g., Gaussian processes) will be explored based on insights
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voiding behavior in mice and developed live imaging techniques to visualize sensory signaling in the bladder wall and dorsal root ganglion (DRG) neurons. In addition, we explore these pathways in human
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adults, significantly impacting quality of life, and remain challenging to treat. Our research group has pioneered innovative methods to study voiding behavior in mice and developed live imaging techniques
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(bio-)chemistry, physics, and engineering expertise to study molecules and cells, taking advantage of optical and single-molecule imaging, molecular probes, molecular biology, and 'large' data analysis
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imaging of mouse and human urothelium, X-ray videocystometry in awake mice, and optogenetic modulation of urothelial cells. The candidate will design and conduct experiments exploring mechanosensitive ion
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protein, cause a broad range of neurogenetic disorders. You will use iPSC-derived neurons to study cytoskeletal abnormalities through cutting-edge microscopy and image analysis, functional assays, and
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investigating sensory signaling in the bladder wall and its role in lower urinary tract disorders (LUTd). The project involves advanced techniques such as ex vivo calcium imaging of mouse and human urothelium, X