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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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supervision across institutions and takes part in three residential schools, methods workshops, monthly research seminars and joint work with organisations beyond academia. Every project includes a planned six
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supervision across institutions and takes part in three residential schools, methods workshops, monthly research seminars and joint work with organisations beyond academia. Every project includes a planned six
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residential schools, methods workshops, monthly research seminars and joint work with organisations beyond academia. Every project includes a planned six-month intersectoral secondment. The doctoral project
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microscopy and SEM, with computational image analysis, computer vision and machine learning. The aim is to develop robust and standardized methods to link structural, mechanical and biological properties
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position within the Human-Centred Artificial Intelligence (HCAI) Lab at NTNU Gjøvik. The position offers an opportunity to conduct mixed method research, applying human-centred design methods and Human
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, receives supervision across institutions and takes part in three residential schools, methods workshops, monthly research seminars and joint work with organisations beyond academia. Every project includes a
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they describe the forest in detail. Traditional inference methods run on finalized, clean data: but a robot needs an answer based only on partial observations. The PhD aims to address this gap, taking machine
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education, research, or knowledge-intensive industry. The position reports to the Unit Leader of Colorlab. About the project The research will address the growing need for reliable methods that can assess the
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develop quantitative methods to estimate effects on infrastructure degradation, maintenance needs, operational risk, punctuality and costs. The aim is to develop and validate a practical, transparent