27 information-technology-"https:"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions at Harvard University
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possible. Basic Qualifications PhD in computer science, statistics, electrical engineering, applied mathematics, computational biology, or a related quantitative field required by the expected start date
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eligible to apply. Deadline Month: April Description: Supports early career scholars working to bring transformative medical research, education, and technology to rid the world of neurological diseases
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multi-photon), viral vectors, protein engineering, mouse models, and multi-omics analyses. For further information on the lab, please visit: www.shigroup.org We welcome applications from postdoctoral
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in the Journal of Neurochemistry (JNC) at the time of a given application round are eligible to apply. In addition, funds can only be transferred if the successful applicant is also an active ISN
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collaboration, this position is based on campus, full-time, at Harvard University. Remote work for this position is not possible. Basic Qualifications PhD in computer science, statistics, electrical engineering
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of the primary objectives of the ITC is to integrate conceptual theory with computational modeling. We are, therefore, interested in candidates working in any field related to theoretical and/or numerical
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Details Title Postdoctoral Scholar in Applied Physics School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Applied Physics Position Description A postdoctoral
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the intersection between quantum information and particle physics. The successful applicant will work in Professor Carlos Argüelles’ group on the development of new algorithms to encode and process particle physics
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builds skills and expertise. We are dedicated to creating a diverse and welcoming environment where everyone can thrive. Why join Harvard Medical School? Harvard Medical School's mission is to nurture a
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developing next-generation AI methods for healthy climate adaptation. The position will focus on building and evaluating foundation models for large-scale spatiotemporal health and environmental data. Our team