40 professor-computer "https:" "https:" "https:" "https:" "https:" "U.S" "St" research jobs at Johns Hopkins University
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of Standards and Technology (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects
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) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires
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are we located in Baltimore, but we also have a presence in Washington, D.C. Connections working at Johns Hopkins University More Jobs from This Employer https://main.hercjobs.org/jobs/22127398/clinical
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applicant will have a PhD in vision science, computer science, or a related field. Experience in cloud-based and mobile image processing for rapid object and face recognition and in use of head-mounted eye
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Baltimore, but we also have a presence in Washington, D.C. Connections working at Johns Hopkins University More Jobs from This Employer https://main.hercjobs.org/jobs/22094247/sr-research-assistant-x28-health
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publications, brief statement of research, and two letters of recommendation. Inquiries may be sent to Professor Chris Overstreet at c.overstreet@jhu.edu. Review of applications will continue until this position
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members of underrepresented groups. Application Materials Required: Further Info: http://physics-astronomy.jhu.edu/ 410-516-7346 The Johns Hopkins University Department of Physics and Astronomy 3400 N
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Hopkins University More Jobs from This Employer https://main.hercjobs.org/jobs/21981957/post-doctoral-fellowship-in-accessible-mri Return to Search Results
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, supernovae, cosmology, or related areas and/or photometry is welcome but not required; strong quantitative and computational skills are essential. The position offers opportunities to lead independent projects
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Professor Fei Lu and Bloomberg Distinguished Professor Mauro Maggioni on topics including mathematical foundations of data science and statistical/machine learning, with an emphasis on inverse problems and in