University of WashingtonResearch Scientist, Integrated Analytics (Temporary) University of WashingtonResearch Scientist, Integrated Analytics (Temporary)Olympia, WARemoteIHME researchers analyze and produce key estimates for their assigned research team and will assess all available relevant quantitative data - including those on causes of death, epidemiology, and a range of determinants such as education and income - from surveys, vital registration, censuses, literature, registries, and administrative records. **Compensation, Benefits and Position Details** **Pay Range Minimum:** $110,016.00 annual **Pay Range Maximum:** $137,460.00 annual **Other Compensation:** - **Benefits:** For information about benefits for this position, visit https://www.washington.edu/jobs/benefits-for-temporary-per-diem-and-less-than-half-time/ **Shift:** First Shift (United States of America) **Temporary or Regular?**
General MotorsNewAV Safety Engineering Analytics Simulation Engineer (GPSSC) General MotorsAV Safety Engineering Analytics Simulation Engineer (GPSSC)Olympia, WAYour Skills & Abilities (Required Qualifications)** + Bachelor's degree in Computer Science, Mechanical Engineering, Vehicle Engineering, Physics, or a related field; or equivalent practical experience + 5+ years of experience working in a field that employs simulation for vehicle development and validation + 5+ years in autonomous vehicles, robotics or related field + Experience in the following: + Simulation: Demonstrated experience with autonomous vehicle simulation platforms, scenario development, + **Programming & Frameworks** : Python, SQL + **Cloud & Big Data:** Extensive experience in cloud-based large scale process including notifications, queuing, serverless cloud functions, event driven processing, code as infrastructure, containerization, process monitoring, process optimization, identity and access management, service to service access, etc. + Collaborate with systems, safety, testing, and autonomy engineering teams to ensure simulation coverage of common and rare driving scenarios and ODD elements + Review simulation results to identify gaps between simulated an real-world performance + Develop methods for leveraging a variety of internal and external data sources for safety monitoring and contribute to the development of a reliable supply chain of continuously flowing data from a variety of sources (internal, external, simulation-based, on-road) to support safety assurance related activities.