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Field
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of integrating advanced optical technologies with machine learning techniques to develop novel, high-performance fibre-optic sensing applications. You will be responsible for the application and validation
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to facilitate the integration of the framework with external systems and educational platforms; Establish a Machine Learning Operations (MLOps) pipeline to automate the lifecycle of models, including training
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of Medicine We focus broadly on quantitative and machine learning techniques in multiple modalities of medical imaging (e.g. fundoscopy images, OCT scans, MRI, CT, X-ray and digital pathology). We bridge
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Intelligence or Machine Learning, with demonstrable analytical skills. Excellent research record evidenced by first-author publications in strong international journals and conferences. Proven experience in
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in coding e.g. Python, or MATLAB Writing skills for research papers. Experience in applied machine learning, fault diagnosis, laboratory testing and development is a plus. Good knowledge in Norwegian
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, master's or Ph.D. in Electrical and Computer Engineering, Computer Science or related field. Solid understanding of wireless communications and networking, including 5G systems, open RAN, and network slicing
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, master's or Ph.D. in Electrical and Computer Engineering, Computer Science or related field. Solid understanding of wireless communications and networking, including 5G systems, open RAN, and network slicing
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About the Opportunity About the Institute Do you want to be part of an exciting new Institute focused on combining human and machine intelligence into working AI solutions? We are launching a
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remodeling. We employ advanced computational and theoretical techniques, such as large scale flow network simulations, machine learning, and methods from topological data analysis, to a broad set of problems
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manufacturing and maturation of cells and engineered tissues at low cost, and simple biofabrication technologies to build clinical-scale constructs. Learn more about the innovative work led by Dr. Chris Chen here