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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 20 hours ago
Rohrbach and T Tuytelaars Code: https://github.com/rahafaljundi/MAS-Memory-Aware-Synapses Theme C Vision&Language learning (selected papers): VisualGPT: Data-efficient Image Captioning by Balancing Visual
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-performance computing is an advantage Strong background in machine learning for image analysis and computer vision, ideally involving microscopy, time-lapse imaging, or other high-dimensional scientific
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 20 hours ago
01, 2022 Description The VCC center at KAUST is looking for postdoctoral researchers and research scientists in Prof. Wonka's research group. The topics of research are computer vision, computer
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image analysis. The position offers opportunities to develop independent research projects, contribute to collaborative grant applications, and prepare for an independent academic or industry career in
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mechanical tests on a dual-actuator loading frame, and acquiring full-field deformation data using three-dimensional digital image correlation (DIC). On the numerical side, this involves building
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for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https
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Challenge grant. The successful candidate will work closely with the Principal Investigators (PIs) to develop and implement innovative research integrating machine learning, computer vision, and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
, scikit-image, Cellpose, PyTorch, TensorFlow, or similar. Special Physical/Mental Requirements Special Instructions For information on UNC Postdoctoral Benefits and Services click here Quick Link https
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software. Preferred qualifications Experience in computer vision, medical-image analysis, echocardiography, ultrasound, cardiac CT, ECG, or another clinical imaging modality. Experience with DICOM, PACS
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frameworks scientific machine learning, inverse problems, differentiable simulation, or physics-based modelling computer vision, biological image analysis, microscopy data, or other noisy high-dimensional