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Field
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conduct in vivo experiments to investigate retinal neurovascular dynamics using the AO-RSO system; Develop or adapt high-speed image acquisition and processing methods for simultaneous measurement
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soils, with applications in permafrost engineering, cold-regions geotechnics, and climate-driven ground processes. The postdoctoral scholar will lead applied modeling and data-constrained analyses using
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systems and Python programming - Skills in data processing and image analysis - Oral and written communication skills, ability to facilitate collaboration at the interface between physics, mathematics, and
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data processing and interpretation workflows. The appointee will also pursue a collaborative science program leveraging the developing instrument capabilities, leading to peer-reviewed publications and
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proposals and reports. Minimum Qualification Ph.D. from an accredited institution in Computer Science, Electrical and Computer Engineering, or a related field with a focus on AI, NLP (natural
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vision for extracting complex patterns, structure, and meaning from images and/or volumes; and (4) new mathematics and algorithms leading to new applications of machine learning and artificial intelligence
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The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to strengthen our research on image recognition, computer vision and deep learning applied
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biology in atherosclerosis. The project will combine patient-derived endothelial colony-forming cells with advanced coronary artery imaging from patients at Barts Health NHS Trust to identify individuals
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: Job Requirements: Required: PhD in computer science, biomedical informatics, electrical engineering, or a related field Demonstrated expertise in machine learning, deep learning, and image-based
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Substantial published experience with PET imaging analysis. Experience with EEG data analysis or digital signal processing. Working knowledge of scientific computing languages, including Matlab, Python