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, Artificial Intelligence , Bayesian Statistics , Big Data , Scientific Machine Learning , Social Sciences , Biomedical Informatics , Causal Inference , Computational Social Science , Data Science and
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records at the TRUST platform (https://trustplatform.sg/) . Large-scale proteomics data have also been generated for these individuals. We are inviting a motivated Research Fellow to join our PRECISE-SG100K
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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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such as Data Science, Statistics, Computer Science, Epidemiology, Environmental Health, or a related field. Demonstrated expertise in large scale analysis and familiarity with health-related datasets
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. · First author of one or more scientific peer-reviewed publications. · Experience working with and jointly analyzing large spatial data sets. · Willingness and demonstrated ability to work collaboratively
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
appropriate statistical analyses and curating large data sets as required, and drafting research papers to disseminate the findings of the project. Co-supervising student projects and providing research support
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’, and to several ML-based projects at the British Antarctic Survey (BAS). There are also strong connections to the Institute for Data and Artificial Intelligence (IDAI) at UoB. Role Summary Implement and
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with collecting and analyzing data gathered from human subjects, both in field, clinic and lab studies as part of evaluations of the technology. A large part of the role will focus on supporting a
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 29 days ago
or large-scale quantitative approaches), and the capacity to articulate and pursue innovative research questions. A demonstrated ability to work both independently and collaboratively, contribute to grant
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of claims data and related large administrative datasets to support policy-relevant research related to mental health and addiction services utilization and quality of care. Experience working with Medicaid