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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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As a fellow you will join our faculty in the Department of Biostatistics, providing statistical support and developing innovative biostatistical methods for research projects at the cutting edge
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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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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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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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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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In compliance with the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act (Clery Act), each year the University of Arizona releases an Annual Security Report (ASR
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(renewable, contingent on performance and funding) will work under the mentorship of Dr. Fei Ye on to conduct quantitative research on development and application of statistical/bioinformatic methodology
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the risks. You will have: a PhD in one of the relevant STEM disciplines, such as mathematics, statistics, computer sciences, theoretical food, ecological or physical sciences, etc. skills in mathematical
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studies. Develop and apply advanced statistical methods and machine learning techniques using tools such as R and Python. Integrate and run process-based models (e.g., crop models, hydrologic models