Job Description Summary: |
The Department of Environmental & Occupational Health is seeking to fill a Postdoctoral Associate position for the research group of Professor Susan Anenberg, Assistant Research Professor Dan Goldberg, and Assistant Research Professor Gaige Kerr. The group's main interests are quantifying health impacts of air pollution and climate change from local to global scales using satellite data and model simulations, including developing scientific methods and evaluating policy scenarios for mitigation. This research is interdisciplinary and draws from a variety of fields, including atmospheric science, chemistry, and public health.
Candidate will be hired to work full-time starting Spring or Summer 2025 for one year with extension for an additional 1-2 years depending on successful performance and sufficient funding. Ability to exercise independent judgment, think critically and logically to overcome problems, and work under minimal supervision is essential.
The primary responsibility is to support federal grants (from
NIH,
NASA, and other agencies) on using satellite remote sensing and chemical transport modeling to characterize air pollution and climate change, and their public health impacts and opportunities for mitigation. This position will work with the group's faculty members in designing and implementing novel studies related to modeling the health implications of present and future climate change and air pollution. The individual will be involved in all aspects of research including directing and performing computer-based modeling work, analyzing and interpreting data, and preparing manuscripts and presentations. In conjunction with Dr. Anenberg, Goldberg, and Kerr, the individual will identify research opportunities and prepare proposals for new extramural funding. The individual will also receive mentoring and direct guidance from Drs. Anenberg, Goldberg, and Kerr in order to advance their career in academic research, public health practice, and/or public policy.
Important geospatial datasets used for this research include chemical transport modeling (e.g. with
CMAQ, CAMx, or
WRF-Chem), satellite remote sensing of environmental characteristics such as air quality (e.g. globally gridded nitrogen dioxide column densities from the Ozone Monitoring Instrument,
OMI, and the TROPOspheric Monitoring Instrument,
TROPOMI), demographic variables (e.g. census block, block group, and tract data from the U.S. Census), and output from environmental models (e.g. gridded air pollution levels over urban, regional, and global areas).
Primary duties and responsibilities include, but are not limited to:
(a) Clean, organize, process, and analyze large datasets in Python, R or similar programming language
(b) Develop publication-quality figures, charts, and tables for high-impact dissemination
Suggest approaches for processing, analyzing, and visualizing data in efficient and effective ways
(d) Identify, review, and suggest available datasets, data servers, and visualization platforms to enhance analyses and communication of results
(e) Support faculty and staff in the research group, as well as external partners, in communicating results, figures, charts, and tables as needed
(f) Plan and conduct independent research; write and publish peer-reviewed manuscripts
(g) Prepare and submit grant proposals
(h) Provide support with data management and computer modeling tasks and guidance to junior staff
(i) Work collaboratively with individuals from diverse disciplines
(j) Other duties as assigned |
Desired Qualifications: |
* A Ph.D. or anticipated Ph.D. by Spring or Summer 2025 in Atmospheric Science, Public Health, Chemistry, Environmental Science/Engineering, or equivalent field with experience in analyzing large geospatial datasets. Salary will be commensurate with training level and experience.
* Excellent data processing and analysis skills using Python, R, or similar programming language
* Experience working with large geospatial datasets (e.g. gridded datasets of environmental variables covering large geographical areas, datasets of demographic information for administrative units)
* Experience creating effective data visualizations for technical and non-technical audiences (e.g. maps, scatterplots, histograms, box plots)
* Experience running a chemical transport model, such as
CMAQ, CAMx, or
WRF-Chem is a plus
* Experience developing web-based tools for interactive data visualizations is a plus
* Excellent verbal communication and follow-up abilities |