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learning, image processing, and electronic hardware verification. They will gain hands-on experience with CT imaging systems, PCB design analysis, and non-destructive testing methods. The project will also
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Education: Ph.D. or M.S. in Computer Science, AI, Computer Vision, or related field Experience: 3+ years in computer vision and deep learning, with specific focus on microscopic imaging, generation
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data science tools. Experience with image analysis, computer programming (Python and R), and machine learning frameworks (TensorFlow, PyTorch). Familiarity with spatial omics, bioimaging data processing
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you will do (Level I): Operate computer software for production of 3D images and multiplanar reconstructions from CT and MRI datasets for optimal visualization of patient’s anatomic structures and
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About us: We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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Additive Technologies) team at University of Warwick seeks a creative and motivated research fellow in the area of deep learning for (X-ray) image processing. The appointment is currently until 31 March 2027
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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for an Artificial Intelligence and Machine Learning (AI/ML) scientist to develop advanced computer vision workflows to support the identification of biomolecules in cryo-electron tomography (cryo-ET) image volumes
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in image processing, quantitative analysis, and biological interpretation Proficiency in AI/machine learning tools for image segmentation, transformation, registration, or tracking Solid mathematical
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available