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experience with empirical research and a strong aptitude for quantitative and technical methods. Experience & competencies Experience with Python and machine learning, preferably applied to medical imaging
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models for high tech industry applications. Your results are expected to be published at leading international venues in machine learning, computer vision, robotics and radar, such as NeurIPS, CVPR, ICRA
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machine learning or computer vision models Technical competencies in one or more of the following: bio-digital systems, biodesign, applied machine learning, computer vision, computational biology, and/or
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applied to computer vision and image analysis. Analytical thinking and problem-structuring skills, including the ability to abstract complex systems, identify core research challenges, and develop
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into the transmission X-ray imaging regime. The developed techniques will be validated on real data. As a candidate, you must have a strong background in machine learning, computational imaging, and/or computer vision
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machine learning and physics to recover nanoscale information from imperfect images? Modern computer chips are built with features only a few nanometers across, yet manufacturers need to measure these
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Machine learning, Image processing, and Computer Vision techniques; Highly motivated to both perform foundational research and apply the developed methods to real-world problems; Highly motivated to work in
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systems and control theory, circuit theory, optimization, and machine learning, with the ultimate goal of advancing the mathematical foundations of physics-based learning. Your responsibilities include
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imaging (crucial) Experience with image segmentation, deep learning, or computer vision. Experience with 3D image processing or inverse problems. Experience with experimental research and data acquisition
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(preferably in Python, including deep learning frameworks such as PyTorch); affinity with medical image analysis and computational modeling; experience with neural networks for image analysis, generative