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to the development of computer platforms that support the prevention, diagnosis and management of endocrine disease (endocrine digital twins), Participants will collaborate closely with other Doctoral Candidates and
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levels. Contributing to the development of computer platforms that support the prevention, diagnosis and management of endocrine disease (endocrine digital twins), Participants will collaborate closely
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and quality issues in real-time. Supporting Digital Twins: Play a crucial role in developing the next generation of computer platforms that support the prevention, diagnosis, and management of endocrine
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to automatically identify, flag, and mitigate data artifacts and quality issues in real-time. Supporting Digital Twins: Play a crucial role in developing the next generation of computer platforms that support the
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will also count when evaluating the candidates. Special requirements for the position The University of Bergen is subject to the regulations for the export control system. The regulation will be applied
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interest in translational endocrinology and digital health technologies Basic programming or data science skills (R, Python) and interest in wearable data analysis are an asset Excellent command of written
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computer science or a related field Command in software design and development in high-level programming languages Knowledge in model-basedas well as data-driven artificial intelligence (symbolic AI and machine
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motivated candidates with: Master’s degree (or equivalent) in computer science or a related field Command in software design and development in high-level programming languages Knowledge in model-basedas well
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from relevant research projects professional programming skills including code version control, unit testing and continuous integration Experience with linux, databases, and server-based computing
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involve a combination of herbarium study, fieldwork including collections and threat assessments, lab work including DNA processing for high-throughput sequencing, bioinformatics including phylogenetic