29 computer-science-quantum "https:" "https:" "https:" "https:" "https:" "University of Waterloo" research jobs at Johns Hopkins University
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Computer/Information Sciences Internal Number: A-179059-11 General Description The Johns Hopkins University Data Science and AI (DSAI) Institute welcomes applications for its Postdoctoral Fellowship program
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. Applications MUST be submitted through: https://careers.udel.edu/en-us/job/502497/post-doctoral-researcher-physics-and-astronomy Application Materials Required: Further Info: http://physics-astronomy.jhu.edu
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work in a number of areas in the foundations of physics or the study of complex systems, including quantum foundations, the emergence of spacetime, theoretical cosmology, origin and evolution
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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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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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interdisciplinary work within the Bloomberg Distinguished Professorships (BDP) program, fostering connections across economics, statistics, and data science. The successful candidate will be encouraged to pursue
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. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science
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Qualifications ? Ph.D. in Physics, Materials Science, or a related field with a concentration in electron microscopy methods ? Experience in the collection and processing of TEM/STEM data ? Computer programming
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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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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