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work on projects funded by Patient-Centered Outcomes Research Institute (PCORI) that aim to develop statistical methods to address methodological challenges in serious illness and palliative care studies
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an available option. Applicants with a range of academic subject backgrounds are welcomed, including natural sciences, epidemiology, engineering, statistics and applied mathematics with experience and
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PhD in STEM Field (including computational or mathematical social science). ? Ability to program in C and Python. ? Must know basic statistics. ? Experience in social network
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Instructions to Applicant Notice of Availability of the Annual Security and Fire Safety Report In compliance with the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act (Clery Act
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Machine Learning, Statistics, Computer Science or closely related discipline. They will demonstrate an ability to publish, including the ability to produce high-quality academic writing. They will have the
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. For more detailed information, please visit our Benefits Page. CAMPUS SECURITY CRIME STATISTICS Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the
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Stanford University / SLAC National Accelerator Laboratory | Menlo Park, California | United States | 2 days ago
or superconducting sensors a plus) Vacuum / noble liquid systems Dilution refrigerators and superconducting detectors Detector simulation using Geant4 and/or G4CMP Statistical data analysis Collaborative experimental
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Special Instructions to Applicant Notice of Availability of the Annual Security and Fire Safety Report In compliance with the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics
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ideal for a researcher with a strong background in survey methodology, experimental design, and statistical analysis who is interested in business power, self-regulation, and public opinion in
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data Experience with GIS/RS and database environments (e.g., ArcGIS and Quantum GIS) Experience with machine learning and statistical learning Experience working with large, diverse datasets Familiarity