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computational (bioinformatics) tools on human and mouse tissues and using in vitro methods on human cells, to explore the consequences of genetics variants on human biology. This is a multi-year position
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Public Health Academic Pipeline Program in Maternal and Child Health (MCH) of the Harvard T.H. Chan School of Public Health (HSPH) invites applications for a full-time postdoctoral training fellowship
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research and recent publications, see the Geometric Machine Learning Group’s website: https://weber.seas.harvard.edu/ . For questions, please email mweber@seas.harvard.edu Applications will be reviewed on a
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effect prediction. The fellow will work under the mentorship of Dr. Alex Luedtke and collaborate with an interdisciplinary team of statisticians, physicians, computer scientists, and health policy
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. Experience with computational text analysis, such as NLP methods, historical text processing, topic modeling, semantic change, or related techniques. Broad interest in cultural evolution, cognitive
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effect prediction. The fellow will work under the mentorship of Dr. Alex Luedtke and collaborate with an interdisciplinary team of statisticians, physicians, computer scientists, and health policy
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Postdoctoral Research Fellow position in statistics, genetics, and biomedical AI. The lab develops cutting-edge theories, methods, and computational tools for integrating large-scale, heterogeneous biomedical
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of our own evolutionary history, while domestication provides an additional window on brain-behavior evolution. The lab uses a variety of experimental and computational tools, such as structural and
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: Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area: Electrical Engineering / Applied Mathematics / Computer Science Position Description: Professors Le Xie and Na Li in
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at the intersection of academia and practice. For more information on D^3, please visit https://d3.harvard.edu/labs . D^3 is looking for candidates with diverse backgrounds and/or new perspectives. There are no