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Machine Learning Group, Department of Engineering, CambridgeMLG Cambridge About Us News Research Publications People PhD Admissions Blog Latest News Papers with MLG authors to appear at ICML and
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environment with researchers from over 100 nationalities Post-docs receive highly competitive salaries and other benefits, inclusive of accommodation, healthcare, medical and dental insurance, relocation
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If you are a current Barnard College employee, please use the internal career site to apply for this position. Job: Post Baccalaureate Fellowship - Barnard Design Center (25-26) Job Summary: The
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Skip to Main Content Favorites : Recently Used Careers Worklist : Main Menu : Search Menu: Menu not sorted. Click to sort in ascending order. Self Service Worklist Reporting Tools Careers : Recent Search Results Refine Search Search Prompt Popup mrs Actions List Popup Home Search Add To Add To...
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Associate Research Fellow / Research Fellow (Military Transformations Programme) The S. Rajaratnam School of International Studies (RSIS), a Graduate School of Nanyang Technological University
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Job Reference: 997149 About the role We are seeking a motivated Research Fellow - Qualitative Data Collection and Analysis to join our NHMRC Assess for Success team. We will be looking to transform assessment and feedback practices for people with acquired brain injury through developing a...
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Responsibilities: To independently undertake research in data privacy, machine learning, and applied cryptography. To produce research papers and reports as required by the funding body or for dissemination
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 23 hours ago
Unit Computer Science Work Location 9201 University City Blvd Vacancy Open To All Candidates Position Designation Post Doc Employment Type Temporary - Full-time Hours per week 40 Work Schedule 8 hours
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Details Title Postdoctoral Fellow in Deep Learning Theory and/or Theoretical Neuroscience School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position
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computational materials science techniques (DFT, MD, machine learning force fields) with data-driven approaches. Design and implement high-throughput experimental workflows for thermal conductivity and phonon