39 multiple-sequence-alignment Fellowship research jobs at Harvard University in United States
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sequencing studies. -Biochemistry. Responsibilities: 1. Conduct research in in vitro or animal models of aging. 2. Publish and present research findings in high-quality scientific journals and conferences. 3
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internal and external meetings Contribute to recommendations on next steps for experiments while also taking an active role overall in program strategy and alignment with the sponsor’s contractual
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, microbiological, or molecular ’omics preferred. Familiarity with methods for high-throughput sequence analysis, ideally microbial community metagenomics and/or microbial genetics. Excellent record of scientific
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Lab of Plant Biodiversity at Harvard University is seeking an exceptional postdoctoral researcher (or research associate) to work with us on the sequencing, identification, and analysis of comparative
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Lab of Plant Biodiversity at Harvard University is seeking an exceptional postdoctoral researcher (or research associate) to work with us on the sequencing, identification, and analysis of comparative
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for postdocs who are performing well and whose research contributions align with ongoing lab goals. Contact Information SB Hiring Team 200 Longwood Avenue Armenise Building 623 Boston MA, 02115 Contact Email
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Together, these research directions seek to reimagine how buildings and cities operate—optimizing energy use, enhancing human well-being, and reducing carbon emissions at scale. We are seeking multiple
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position based in Boston, with the possibility of extension. The position will be considered hybrid, requiring several days in the Boston office in addition to virtual workdays to align with the team’s
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degree recipients interested in working to address the multiple challenges of inequality. This program intends to seed new research directions; facilitate collaboration and mentorship across disciplines
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background. The ideal candidate will have existing expertise in several of the following areas, aligned with our research focus: 1) Causal inference, invariant learning and representation learning