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Field
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Mississippi. Apply computer vision and machine learning approaches to integrate ground-based imagery, remote sensing data, and lidar data for high-resolution flood detection and mapping. Develop and calibrate
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members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL | Opportunities for Veterans at Brookhaven National Laboratory . Equal
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. Essential qualifications: PhD in Computer Science, Robotics, Machine Learning, or related fields. Programming skills in Python/C++ and experience with ML frameworks (e.g. PyTorch, TensorFlow, JAX). Strong
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
of Computer Science at the University of North Carolina at Chapel Hill seeks a talented, highly motivated postdoctoral researcher with a background in machine learning and/or biomedical image processing. The ACM Lab is
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
of Computer Science at the University of North Carolina at Chapel Hill seeks a talented, highly motivated postdoctoral researcher with a background in machine learning and/or biomedical image processing. The ACM Lab is
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Description The Laboratory for Computer-Human Intelligence (CHI-lab, https://www.x-labs.xyz ) in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
the group of Dr. Tengfei Li at the University of North Carolina at Chapel Hill. The successful candidate will develop and apply advanced statistical and machine learning methods for infant cognitive
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. Qualifications: PhD in machine learning, with experience in applications in computer vision or medical image analysis. Strong publication record in top venues (e.g., CVPR, MIDL, MICCAI, IPMI, PAMI, TMI, MIA
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transcriptomics data analysis. Experience in quantitative image analysis, computer vision, or digital pathology. A strong background in cancer biology or immunology. Experience with machine learning, deep learning
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computer vision and machine learning approaches to integrate ground-based imagery, remote sensing data, and lidar data for high-resolution flood detection and mapping. Develop and calibrate hydraulic flood