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related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with deep learning, computer vision, medical image analysis
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deep learning, computer vision, medical image analysis or unsupervised learning is an advantage. English language skills, both written and spoken Qualification requirements PhD stipends are allocated
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Generative Artificial Intelligence (GAI) is rapidly transforming higher education, yet most current GAI systems are designed to support individual productivity rather than collaborative learning
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Generative Artificial Intelligence (GAI) is rapidly transforming higher education, yet most current GAI systems are designed to support individual productivity rather than collaborative learning
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PhD Scholarship in University Students’ Learning Via Digital Twins of Neutron Scattering Instruments
Are you passionate about how to train university students for neutron-based investigation at the European Spallation Source (ESS) in Lund? Do you want to research how students learn via digital
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applicants who demonstrate substantial hands-on experience implementing, training and evaluating deep-learning models will be considered. General interest in AI or experience limited to running tutorials
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globally recognised business school with deep roots in the Nordic socio-economic model. Our faculty has a broad focus on societal challenges, and we have earned a reputation for high-quality disciplinary and
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, mathematics, biology, and epidemiology, developing and applying novel statistical methods and deep learning approaches for global health challenges. The group’s research spans disease modelling, genomic
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advanced analytical approaches, including deep learning and machine learning, to improve disease subtyping and risk prediction. You should have a strong willingness to learn, enjoy tackling challenging
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within the newly funded Horizon Europe research project OceanSOS (creating a Safe Operating Space for the deep and open Ocean). OceanSOS is an international, interdisciplinary research project