443 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Harvard University in United States
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DNA elements and transcriptional and chromatin remodeling machinery in gene regulation. More information about the lab and specific research areas can be found at https://adelman.hms.harvard.edu
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membranes. Please see https://blacklow.hms.harvard.edu/ for additional information on areas of research. We welcome applications from recent PhD graduates who are interested in these or related fields
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of cilia. More information about the lab and specific project areas can be found at https://brown.hms.harvard.edu/research. We welcome applications from recent PhD graduates, particularly those who may
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development. More information about the lab and specific research areas can be found at https://sites.harvard.edu/zheng/. We welcome applications from recent chemistry or chemical biology PhD graduates with
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relevant field and the ability to teach effectively in a policy-focused, professional school environment. Applicants should submit a CV and teaching evaluations to https://academicpositions.harvard.edu
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integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing of grants and
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-determination. In-depth consultation with community leaders, health experts, and other local knowledge carriers—and circulation of lessons learned through routine academic publication and community dissemination
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applicants for a postdoctoral fellow position in the Laboratory of Systems Pharmacology (LSP; https://labsyspharm.org/ ), part of the Harvard Program in Therapeutic Science, at Harvard Medical School in Boston
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) of focused, independent research. Fellows enjoy access to Harvard’s vast research resources and vibrant intellectual environment. Basic Qualifications Please see the fellowship page for more information: https
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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning