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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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RE-C05-i08 do Programa de Recuperação e Resiliência, através da Fundação para a Ciência e a Tecnologia - FCT, nas seguintes condições: Scientific Area: Computer Engineering, Biomedical Engineering
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optimization. Experience with quality-diversity methods is a plus. • Experience with machine learning and artificial intelligence. • Strong programming skills (e.g., Python, C++), and familiarity with ROS
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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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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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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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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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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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, 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