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large number of data sets across many data modalities as well as large user audiences and collaborators who are leading experts in their biomedical domains. We are also working with many individual
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large number of data sets across many data modalities as well as large user audiences and collaborators who are leading experts in their biomedical domains. We are also working with many individual
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to analyze large multi-modal datasets and/or who wish to deploy the next generation of exposome AI models. These positions come with data ready to analyze: the candidate can focus on developing research
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position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic
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scalable bioinformatics pipelines on cloud-based infrastructure. The Research Fellow will be responsible for the code base supporting the large-scale genomic processing and analysis pipelines at the SMaHT
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. or M.D./Ph.D. in areas such as Data Science, Statistics, Computer Science, Epidemiology, Environmental Health, or a related field. Demonstrated expertise in large scale analysis and familiarity with health
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molecular and phenotype data. Including code that is production-ready for dissemination to other laboratories and for diagnostic use, and the management of large-scale data. They will join a team of