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the Department of Defense (DoD), other US Government agencies, private companies, and data producers from federal agencies and academia. This is a one year position renewable for up to three years. Continuation in
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Discovery, Development Sciences, and Aesthetics which includes fields such as chemistry, biology, pharmaceutical science, and computational information sciences. This enriching training program offers a
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medical physics, computer science, biomedical engineering, electrical engineering, applied mathematics, or a related field; or an MD with significant research experience and deep familiarity with AI
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for faculty positions in mathematics and related interdisciplinary areas, including but not limited to: Computational and applied mathematics; artificial intelligence for sciences (especially biomedical science
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, bioethics) Priority consideration will be assigned to applicants who have completed the PhD in the three years prior to the start date Experience working in low-income communities Additional Qualifications
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. Kostylev , Arnoldo Frigessi Working language: English. This position is at the University of Oslo, Integreat – Norwegian Centre for Knowledge-driven Machine Learning, and the Department of Informatics, with
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information from electronic health records Conduct systems biology research and analysis for high dimensional data Required Qualifications* PhD degree or higher in computer science, biomedical informatics
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for a fixed term up to end of June 2028, ideally starting in September 2025. The position comes with an allowance to cover international travel and computing. Role Summary We are seeking to appoint
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innovative research programmes. You may also: Hold a PhD in genetics, pathology, cancer cell biology, computer science, data science, or a related discipline. Have a significant research profile with a strong
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collaborate with First Peoples that partner with the Water Justice Hub. Ideal candidate Our ideal candidate will hold a PhD in economics, with a demonstrated record of independent research and relevant