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. General Description of the DDLS Program Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular
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the past ten years thanks to artificial intelligence, mainly in the form of deep convolutional neural networks. In parallel, functional analysis of tissue samples via novel microscopy techniques and spatial
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program Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes
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(DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global
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researcher to join our research team in exploring the intersection of cybersecurity and artificial intelligence (AI) with a human-centered focus. The position is shared between the Cybersecurity and Privacy
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. The department is BTH's largest department, with 70 people. The research at the department is conducted in four major areas: artificial intelligence and machine learning, cloud computing and distributed systems
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research school. Data driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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driving the integration of methods in artificial intelligence (AI) and machine learning (ML) to improve and optimize workflows when developing therapeutic antibodies. Duties – what we expect from you As an
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-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human
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National Program for Data Driven Life Science (DDLS). About the DDLS Fellows program Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems