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independently. Merits: Education or training in computer vision, machine learning, deep learning, bioinformatics, advanced microscopy, cell biology, or RNA biology. Education in mathematical statistics
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biomedical engineering, electrical engineering, machine learning, statistics, computer science, or a related area considered relevant for the research topic, or completed courses with a minimum of 240 credits
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Join MultiD Analyses AB and the University of Gothenburg to develop innovative bioinformatics and machine learning methods for RNA Fragmentomics, with the ambition to improve cancer care through
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development projects. The work as a PhD student in Machine Elements is mainly experimental, which requires good practical skills as well as detailed knowledge of tribology, tribological tests, surface analysis
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of algorithms, data structures, high-performance computing, machine learning and microbiology. The position at the Department of Molecular Biology at Umeå University is temporary for four years to start
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to try out the role of a teacher. As a researcher, you work as a neutral party in many contexts, which provides a fantastic opportunity to learn how to run challenging development projects. The work as a PhD
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between biology and artificial intelligence. Strong collaborative skills, analytical ability, and the capacity to work independently. Merits: Education or training in computer vision, machine learning, deep
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methods (e.g. machine learning methods and many other methods) to harmonize historical and current pathogen nomenclature, standardize laboratory test methods and result vocabularies, and translate clinical
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, and registry-linked outcome data. In this project, you will develop and apply AI-based methods (e.g. machine learning methods and many other methods) to harmonize historical and current pathogen
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‑mining and machine‑learning methods. The expected scientific outcome is to establish guidelines for identifying and optimizing promising electrolyte materials and to support the development of future