37 phd-studenship-in-computer-vision-and-machine-learning PhD positions at SciLifeLab
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the Knut and Alice Wallenberg (KAW) Foundation. In 2025 the DDLS Research School will be expanded with the recruitment of 19 academic and 7 industrial PhD students. During the course of the DDLS program more
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the Knut and Alice Wallenberg (KAW) Foundation. In 2025 the DDLS Research School will be expanded with the recruitment of 19 academic and 7 industrial PhD students. During the course of the DDLS program more
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vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid
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of image analysis and machine learning with a minimum of 90 higher education credits. Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural
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will combine state-of-the-art computer vision, modeling and archived specimens to determine biotic and abiotic factors driving spatial variation in molt phenology. It will use museum genomics to recover
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on applying AI and machine learning to molecular design challenges. This position is one of several industrial PhD roles funded by the DDLS program, which supports training in four strategic areas: cell and
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biology. The applicant should also have an interest in learning, or previous experience in, computer programming, particularly using languages such as Python. The ideal candidate is driven and a creative
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas
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at a maximum level of 20 %. Requirements To meet the entry requirements for doctoral studies, you must hold a Master’s (second-cycle) degree in Machine learning, Computer science, Bioinformatics