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Field
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software development team A published example of a developed algorithm, pipeline, or database with application to multi-omic or image data. Ideally an R package in CRAN or Bioconductor. Demonstrated ability
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progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and
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scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities
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cookie er ikke et program som kan inneholde skadelige programmer eller virus. Hvordan nettsiden bruker cookies Cookies er nødvendig for å få nettsiden til å fungere. Cookies hjelper oss å få en oversikt
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for testing newly developed algorithms is anticipated in mainland Norway, Svalbard, and abroad. Funding is also available for conference attendances and research visits with external collaborators. The position
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. To probe such regimes requires the development of fast and scalable algorithms for many-component systems, and of coarse-grained models that can be analyzed and simulated. Strong applicants with backgrounds
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on the development of machine learning algorithms, particularly transfer and adaptive learning, for multimodal wearable biosensing and its translation to rehabilitation and digital health applications. It is co
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Researcher will be based out of either the Boston, MA or Portland, ME campus and conduct applied research, prepare work for submission to journal/conference publications, contribute to extramural funding
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these technologies have for human expertise, and how professionals learn to work with these technologies in constructive and trustworthy ways. Emerging epistemic technologies such as algorithmic or AI-powered