Postdoctoral Scholar - Environmental Health Sciences - School of Public Health
Position: Postdoctoral Scholar - Employee Location: University of California, Berkeley, CA Salary: Commensurate with experience Target State date: April 2020
The Division of Environmental Health Sciences at the School of Public Health at the University of California, Berkeley seeks applications for a Postdoctoral Scholar-Employee, in the area of remote sensing, exposure assessment, and environmental health, at full-time with an expected start date of April 2020.
The Postdoc would join an exciting new project investigating on-road vehicle emissions of criteria pollutants from tailpipes and trace metals from non-tailpipe sources, and their impacts on daily respiratory disease symptoms in California. Funded by the California Air Resources Board (CARB), collaborators from the University of California, Berkeley (PI Dr. Jason Su and key investigator Dr. John Balmes) and Propeller Health (PI Dr. Meredith Barrett) will work collaboratively to investigate 1) the temporal and spatial patterns of inhaled medication use, collected by digital sensors, 2) associated activity space for participants across California, and 3) associations of inhaled medication use with tailpipe and non-tailpipe vehicle emissions. Daily linear mixed-effects land-use regression models will be developed through incorporating a comprehensive data source including remote sensing data, land use and land cover data, traffic and pollen data, criteria air pollutants, trace metals, stationary sources of emissions, highway pavement conditions data, and hourly and daily weather data. In health outcome modeling, both traditional environmental epidemiology models (e.g., linear mixed models) and advanced machine learning models (e.g., random forest models) will be used in the modeling process and compared with prediction powers. The results of this project will help CARB characterize the health effects of its regulatory programs, and help identify disproportionately exposed communities and their related sources. More importantly, it will also provide the information needed to include respiratory disease symptoms as a new endpoint for CARB's health analyses in its regulatory processes.
The Postdoctoral Scholar would also contribute to a number of technical areas related to air pollution science, exposure science, epidemiology, and environmental health. Examples of technical areas where highly qualified candidates might contribute include: Knowledge in acquiring and processing land use, land cover, weather and traffic data from various sources for use in land-use regression model development; Analyzing daily and hourly traffic data from the California Department of Transportation (Caltrans) Performance Measurement System (PeMS); Linking traffic or other data to temporal environmental data layers through R or Python programming; Developing daily land-use regression models through R or Python programming; Carrying out random forest modeling, implementing deletion/substitution/addition algorithms or performing mixed-effects modeling; Analyzing respiratory symptom data through R or Python programming; Identifying time and location of environmental triggers; Modeling environmental triggers of respiratory symptoms through both traditional linear mixed models and machine learning techniques, such as random forest modeling techniques. Basic qualifications (at time of application): advanced degree or enrolled in an advanced degree program.
Basic qualification (at time of application):
Ph.D. (or equivalent international degree, or enrolled in a Ph.D. (or equivalent international degree) granting program at the time of application.
Ph.D. in air pollution science, exposure science, epidemiology, or environmental health.
Experience in acquiring and processing remote sensing data such as tropospheric column densities of NO2 from the Ozone Monitoring Instrument (OMI), Aerosol Optical Depth (AOD) data from the Multiangle Implementation of Atmospheric Correction (MAIAC) algorithm, and ozone data from the National Oceanic and Atmospheric Administration (NOAA) National Weather Services.
Previous experience with remote sensing data analysis skills includes but is not limited to satellite data orthorectification, filling data gaps through temporal convolution with Gaussian kernels, and developing linear and non-linear mixed prediction models for days without effective measurements.
This position is full-time for a one-year term with the possibility of renewal, contingent on performance and availability of funding. The total duration of an individual's postdoctoral service may not exceed five years including postdoctoral service at other institutions.
Letters of reference may be solicited for finalists. All letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality (http://apo.berkeley.edu/evalltr.html(link is external)) prior to submitting their letters.
The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status. For the complete University of California nondiscrimination and affirmative action, policy see: http://policy.ucop.edu/doc/4000376/NondiscrimAffirmAct(link is external).
UC Postdocs are exclusively represented by the United Auto Workers Local (5810).
Diversity, equity, and inclusion are core values at UC Berkeley and The School of Public Health. Our excellence can only be fully realized by faculty, students, and staff who share our commitment to these values. Successful candidates for our academic positions will demonstrate evidence of a commitment to advancing equity and inclusion.
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