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materials must be submitted here to this Interfolio listing: https://apply.interfolio.com/187576 . Only materials submitted through the Interfolio link will be reviewed. Do not submit materials
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Center for Astrophysics | Harvard & Smithsonian | Cambridge, Massachusetts | United States | about 20 hours ago
and space-based astronomy, engineering and technology development, and education. The research objectives of the CfA are carried out primarily with support from the federal government, the Smithsonian
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– from ecosystems to microbiology and developmental biology, from evolution to cell biology, from molecular biology to systems biology, bioinformatics, and genomics. It is always an exciting time for
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to explore the dynamics of tropical forests responding and feeding back to climate. The position is part of the NGEE-Tropics project (https://ngee-tropics.lbl.gov ), a long-term, DOE-funded effort to
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education. Technology is developing rapidly, raising profound and urgent questions about what it means to live a flourishing life: What makes humans distinct? What does community look like in an increasingly
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new technology or perspective to bear on the work in the lab. The successful candidate will work with Dr. von Andrian to develop an independent research project within the scope of the lab’s research
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applications for a Postdoctoral Fellow to join the Human Evolutionary and Statistical Genetics (HESG) Lab. The HESG Lab develops statistical and computational methods to understand human population history and
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in the Klein lab at Harvard Medical School in Boston Massachusetts. The work of the Klein lab is focused on revealing the molecular and environmental rules governing cell fate decisions in development
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analyzing hyperspectral data and developing machine learning models - Genetic or molecular lab experience - Bioinformatics, or statistical genetics experience - Excellent written and oral communication skills
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Challenge grant. The successful candidate will work closely with the Principal Investigators (PIs) to develop and implement innovative research integrating machine learning, computer vision, and wildlife