370 structural-engineering-"https:" "https:" "https:" "Simons Foundation" positions at Harvard University
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that arise, and contribute intellectually to the project. For more information, visit: https://wyss.harvard.edu/focus-area/biomimetic-therapeutic-diagnostics/ What you'll do: Perform microfluidic organ-on-chip
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information: http://www.hbs.edu/information-technology/about-us Job Description Are you excited by the idea of joining a world-class organization at the intersection of higher education and technology? Are
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the Institutional Risk Management (IRM) program which provides a structured process for identifying, assessing, prioritizing and managing risks across various levels of the University. The person in this role will
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(https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods
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Harvard University, School of Engineering and Applied Science Position ID: SEAS-TENPROFAM [#27841] Position Title: Position Type: Tenured/Tenure-track faculty Position Location: Cambridge
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https://d3.harvard.edu and https://d3.harvard.edu/lish/ . Research Focus: Postdoctoral Fellows at D^3 will conduct research at the intersection of innovation, digital transformation, and artificial
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operations; technology services; human resources; enrollment and admissions; and finance. Job Description Job Summary The Program Administrator, Engagements plays a critical role in the planning and delivery
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, particularly those who could bring a new technology or perspective to bear on the work in the lab. Ideally the applicant would have experience in some or all of the following techniques: (1) Neuropixel
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about the lab, please visit https://www.hsph.harvard.edu/onnela-lab/ . Contact Information Hassan Dawood Contact Email hdawood@hsph.harvard.edu Salary Range $75,000/year Minimum Number of References
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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