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executed, ideally involving 3D image analysis, inverse problems, or physics-informed modeling. Cryo-EM/ET and computational structural biology projects are especially relevant. Discuss results
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, including image registration, motion correction, segmentation and signal extraction, quality control, longitudinal tracking where appropriate, and quantitative analysis of neural population dynamics. Help
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contexts. Collaborate on DICOM/image processing and segmentation tasks as needed. Gathers customer information and determines customer’s issue by analyzing the symptoms and identifying/resolving the
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focus on the following three main tasks:(a) Developing deep learning pipelines for multilayer segmentation and nanoscale transistor classification from microscopy images; (b) Designing graph-based
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data segmentation and automation, and ensure compliance with email best practices. With expertise in web development, digital marketing, and data-driven strategy, this position enhances the
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, neural networks) for spectral interpretation, segmentation, and material identification. • Create and curate a dedicated HSI spectral library for cultural heritage materials, linking reference samples
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cardiac structures including CT and DT-MRI segmentation, reconstruction and related analysis. § Biaxial mechanical characterisation of vascular and valvular tissue. § Working as a Technical Lead to design
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, artificial intelligence, and data-driven discovery. Learn more about the iMIND Study Team: https://dukeeyecenter.duke.edu/imind Be Bold. Join a multidisciplinary research team at the forefront of
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maintain workflows for 10x Genomics (preferably scRNAseq, Xenium, scATAC and multi-ome), smartseq datasets; related experience in image and transcript quality control, cell segmentation assessment
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a focus on microscopy image analysis. Specifically, we are interested in the development of new methods to identify structures of interest in large datasets (detection, segmentation, and tracking