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research, addressing the big data and artificial intelligence challenges of our industry partners. Field of subject for the position: Computer Science Placement: Department of Computer Science and Media
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Stanford University / SLAC National Accelerator Laboratory | Menlo Park, California | United States | 3 days ago
-QIS [#29764] Position Title: Position Location: Menlo Park, California 94025, United States of America [map ] Subject Area: Quantum Information Science Appl Deadline: 2025/08/31 11:59PM (posted 2025
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Posting Details Position Information Fiscal Year 2024-2025 Position Title Postdoctoral Associate, Biomedical Informatics Department Classification Title Postdoctoral Associate Department Biomedical
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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at the University of Arizona invites applications for a Postdoctoral Research Associate position in theoretical nuclear physics and quantum information science, beginning in Fall 2025 or later. The successful
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. Qualifications requirements The applicant is required to have a PhD degree in Computer Science, Software Engineering, or related fields. The applicant must have completed the degree no more than three years before
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Classification Title: Postdoctoral Associate Classification Minimum Requirements: A Ph.D. in biomedical informatics, computer science, information science, data science, (bio)-statistics, (applied
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 25-Jul-25 Location: Irvine, California Type: Full-time Categories: Academic/Faculty Engineering Internal Number
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Job Description Join the Multi-omics Network Analytics Research Team as a Postdoc in Computational Biology at the Danish Technical University (DTU) Are you an experienced scientist with a passion
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Computer science, Biostatistics, Bioinformatics, Neuroscience, or similar field. Proficiency in written and spoken English. Previous work with large-scale data analysis, integration and visualization. Proficiency in