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computational image analysis, computer vision and machine learning. The aim is to develop robust and standardized methods to link structural, mechanical and biological properties to biomaterial performance and
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, and regenerative constructs. The project combines advanced 2D and 3D bioimaging, including micro/nanoCT, confocal microscopy and SEM, with computational image analysis, computer vision and machine
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backgrounds include, but are not limited to, communication, media studies, human-computer interaction, information systems, sociology, psychology, management, organisational behaviour, human resource management
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include, but are not limited to, communication, media studies, human-computer interaction, information systems, sociology, psychology, management, organisational behaviour, human resource management, law
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specialisation in Communication. Relevant disciplinary backgrounds include, but are not limited to, communication, media studies, human-computer interaction, information systems, sociology, psychology, management
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modeling, computer simulation, non-linear model analysis, interactive learning environments and decision-laboratory experiments. About the project/work tasks: Description of the INTEGRATOR project
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population genetics and marine metapopulation dynamics. Contribute to generating and managing reproducible computer code and workflows. Produce a high-quality PhD thesis, comprising of manuscripts suitable
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Doctoral Programme, see Section 6-1 of the PhD regulations for more information. You must have a master's degree or equivalent in computer science, artificial intelligence, machine learning, computer vision
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CAD tools Finite-element analysis and simulation Rapid prototyping and additive manufacturing Signal processing and data analytics, control systems Machine learning or computer vision Product
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Signal processing and data analytics, control systems Machine learning or computer vision Product development in multidisciplinary engineering teams. Responsibility teams Exposure to globally leading