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machine learning methods are a plus. Qualifications: PhD in neuroscience, or related fields DeepLabCut or similar methods Demonstrated hands-on experience with 2-photon imaging techniques Experience
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for image-based modelling Your profile PhD in physics, materials science, computer science, applied mathematics or a related field strong background in image processing and analysis, including deep learning
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of motion analysis in collaboration processing of images in preparation for image-based modelling Your profile PhD in physics, materials science, computer science, applied mathematics or a related field
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to help prevent, diagnose and treat illnesses such as cancer, heart disease, infectious diseases and neurodegenerative conditions. The Crick is a place for collaboration, innovation and exploration across
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the scope of BlueMat, taking advantage of the collaborative network within the excellence cluster Your profile PhD in physics or in a related discipline experience in phase contrast or coherent X-ray imaging
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), proteomics (LC-MS/MS), (epi)genomic data processing, multi-omics integration, machine learning approaches for high-dimensional data, confocal / two-photon imaging, tissue clearing and light-sheet microscopy
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Research Centre (CRC) 1450 “inSight – Multiscale imaging of organ-specific inflammation” (https://www.uni-muenster.de/CRC-inSight) The project is based in the research group of Prof. Dr. Kerstin Steinbrink
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-performing design variants Build and characterize prototype devices and correlate results with model predictions Run calibration work with documented uncertainty and reproducibility expectations Execute
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an expert in the extracellular vesicle field with skills in genetic engineering of extracellular vesicles (including transient/stable transgenesis of zebrafish), live embryo imaging, and spatial
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histology or imaging techniques. ⦁ Familiarity with R or other statistical tools for data analysis. The postdoctoral researcher and PhD-student positions are initially limited to 2 and 4 years