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developing next-generation AI methods for healthy climate adaptation. The position will focus on building and evaluating foundation models for large-scale spatiotemporal health and environmental data. Our team
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Details Title Postdoctoral Fellow, Digital, Data, and Design Institute - Digital Reskilling Lab School Harvard Business School Department/Area Position Description The Digital Reskilling Lab, led by
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large administrative or claims data (e.g., Medicaid, commercial claims, or similar) Clear scientific writing and communication; a track record of publications Special Instructions Please include: · CV
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for analysis of large-scale whole genome genetic and genomic and phenotype data. Examples include large Whole Genome Sequencing association studies, biobanks, single-cell and CRISPR multiome data, integrative
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large-scale genetic screening in our research approach. Basic Qualifications 1. A Ph.D. in a relevant field 2. Demonstrated record of research achievement. 3. Strong written and oral communication skills
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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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, machine learning and AI, statistical computing, big data and AI applications and prediction in biology, medicine and infectious diseases. Potential research projects include (but are not limited
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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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motivated Postdoctoral Research Fellow to develop and apply innovative, data-driven models for seismology, with a focus on developing cutting-edge foundation models. This is an exceptional opportunity
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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