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skills, be service-oriented, and structured. We require you to have an academic degree (3–6 years), preferably in medicine. Proficiency in Swedish, both spoken and written, as well as excellent English
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learning (DL) workflows for extracting, curating, and learning from structured and non-structured polymer data, Develop data-efficient representations for polymers for use in ML models, Develop ML models
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safety at the facility and enjoy supporting colleagues with clear, constructive guidance. You communicate effectively, build trust across functions, and bring a structured, quality-conscious approach
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facility. You communicate clearly and enjoy building relationships across different functions. You are structured, quality-conscious, and detail-oriented, with a strong commitment to safety and compliance
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. Subject description Computer Science includes research on algorithms, data structures, computing models and software engineering for the development of resource-efficient, distributed and intelligent system
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, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. SciLifeLab and
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structures in inflammatory diseases and cancer. The successful candidate will join a growing collaborative research group, who works closely with researchers in the Department of Gene Technology, SciLifeLab
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of English. It is an advantage if you have: Experience of working with large text or image materials, for example organising digital archives, curating public databases, structuring and quality-assuring large
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to the project (petrography, EPMA, LA-ICP-MS, isotopes, etc.) - Strong publication record relative to career stage Other merits - Experience of teaching - Experience with fieldwork, structural or stratigraphic
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scale longitudinal surveys on ageing and health. Some analyses will be also carried out using register data. For more information about the HEALFAM-project, see: https://sites.google.com/view/healfam/home