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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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to various personnel throughout the University. Basic computer skills required, including familiarity with navigating web-based applications. Eligibility for ALAT certification preferred. Additional
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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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basis until the position is filled. For more information, please visit our website, https://topo.chemistry.harvard.edu/ . Please note: This position is contingent upon funding and satisfactory
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the time the appointment begins. Additional Qualifications Demonstrated strong commitment to teaching is desired. Special Instructions Please submit the following materials through the ARIeS portal (https
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desired. Special Instructions Required materials, to be submitted through the ARIeS portal (https://academicpositions.harvard.edu/postings/15712 ): 1. Cover letter 2. Curriculum Vitae 3. Writing sample
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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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, account access, collaboration tools, classroom technology, networking, phones and voice mail, IT security, computer asset lifecycle, device lending, shared device and printer support, and classroom and
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. The successful applicant will be expected to develop an innovative research program in sequential decision making. Our lab is involved in digital health studies in dental health, cardiac health, physical activity
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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