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, or digital health. Responsibilities The Postdoctoral Scholar will: Analyze large-scale datasets from cohorts and clinical trials, including longitudinal data. Develop and implement predictive models
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19 Aug 2026 Job Information Organisation/Company Luleå tekniska universitet Research Field Engineering Researcher Profile First Stage Researcher (R1) Application Deadline 9 Sep 2026 - 12:00 (UTC
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Work Schedule: Monday – Friday, 8 a.m. – 5 p.m. Summary The lab is seeking a postdoctoral researcher to collaborate on groundbreaking projects integrating patient-level data with artificial intelligence
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we invent it. If you're passionate about joining a community that challenges the
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Postdoctoral researcher (17 months): Ethics and Epistemology of LLMs4EU: Design, Data and Deployment
regarding language technologies and especially Large Language Models (LLMs), a market currently dominated by U.S. companies. The project builds on existing European initiatives to ensure LLMs, and their
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proteins and pathways implicated on disease pathogenesis. We are currently analyzing brain, CSF and blood, multi-omic data (transcriptomics, proteomics and metabolomics), from a large collection of well
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in developmental/educational psychology. They should also have the experiences of overseeing the implementation of a large-scale research project. Knowledge and experience in assessment development
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support the research and implementation of a large-scale mental health and well-being project for primary schools in Hong Kong under the Department of Psychology, Faculty of Social Sciences. Major tasks
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, implement and benchmark machine learning models for large-scale health datasets consisting of diverse information including structured medical history, demographics, clinical notes, laboratory measurements
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. Responsibilities: Conduct empirical research on responses to hazardous weather using mobility data Clean, manage, and analyze large mobility datasets using python and modern econometric and computational tools