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Research Fellow - Advanced Signal Processing and Machine Learning Techniques for Vital Signs Measurement from Video Images Job No.: 691722 Location: Clayton campus Employment Type: Full-time
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engineering, as well as computer vision, imaging, hyperspectral imaging, machine learning techniques in food and agricultural area, is desired. A understanding of modern AI model development Stipend $70,000.00
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systems using computer vision, quantitative image analysis, deep learning methods for detection, diagnosis, and quantitative analysis of abnormalities with multimodal data, including clinical and
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for publication. Preferred qualifications: Experience with super-resolution microscopy, coding (Phyton, Matlab), and machine learning is preferred. City of Hope employees pay is based on the following criteria
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-processing using conventional and deep-learning based approaches. Coordinate MR imaging studies to promote applications of MRI in the application of radiotherapy. Assist in clinical radiation therapy physics
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qualification; (ii) demonstrate research skills in imaging science and machine learning, particularly on image reverse engineering, fake image and video detection, statistical detection models and mathematical
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practical experience in deep learning-based machine learning or natural language processing. Strong background in statistical modeling. Strong scientific writing skills. Expertise in medical imaging
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such as Wazuh and MXOC Apply advanced machine learning techniques (e.g., reinforcement learning, generative AI, and interpretable AI) to enhance system adaptability and performance Collaborate with industry
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degree will definitely be advantageous. Knowledge of machine learning, pytorch, huggingface etc... Knowledge of image processing is required. Ability to effectively and efficiently utilise industry
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of this programme. The profile PhD in computer vision, computational biology, physics or a related discipline Demonstrated expertise in image analysis and working with large-scale imaging datasets Strong expertise in