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Technology, Campus Norrköping. Your work assignments This position is motivated by the need for reliable visualization and data analysis methods that support understanding of the increasing amount
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machine learning, computer vision, and materials science. The focus of this position is on development of neuro-symbolic models for the effective behaviour of the complex microstructure of recycled
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for advanced courses, international research visits, and networking across Sweden’s top universities. Information about the research group The Computer Vision Group at the division of Signal processing and
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microanalysis methods to reveal how tramp elements introduced during recycling impact microstructure and properties in aluminium mega-castings. As a PhD student, you will be supported by a multidisciplinary team
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well-equipped laboratory facilities for research and a good inter-disciplinary academic network in Sweden and abroad. Subject description Machine learning focuses on computational methods by which
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the fields of cloud computing, computer networking and immersive systems to develop elastic and cost-efficient cloud-based AI pipeline to tackle climate change and support sustainability. Some of the tasks
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the fields of cloud computing, computer networking and immersive systems to develop elastic and cost-efficient cloud-based AI pipeline to tackle climate change and support sustainability. Some of the tasks
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of recycled aluminium. More specifically, the project will focus on advanced numerical methods to understand how defects and different microstructures affect the strength of mega-cast components. As a PhD
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knowledge in at least two of the following areas: extended reality, perception, psychophysical and psychophysiological methods, experimental design, and human-computer interaction. Good knowledge in one
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project: Computational methods for complex SV detection using sequencing data Main supervisor: Kristoffer Sahlin, ksahlin@math.su.se . Co-supervisor: Adam Ameur, adam.ameur@igp.uu.se . In the Department