Post Doctoral Associate
Job Description
Position Number:
129041Title:
Post-Doctoral AssociateFunctional Title:
Post Doctoral AssociateCategory Status:
15-Fac.Non-Tenured,Continuing ConApplicant Search Category:
FacultyUniversity Authorized FTE:
100Unit:
SPHL-Epidemiology & BiostatisticsCampus/College Information:
Founded in 1856, University of Maryland, College Park is the state’s flagship institution. Our 1,250-acre College Park campus is just minutes away from Washington, D.C., and the nexus of the nation’s legislative, executive, and judicial centers of power. This unique proximity to business and technology leaders, federal departments and agencies, and a myriad of research entities, embassies, think tanks, cultural centers, and non-profit organizations is simply unparalleled. Synergistic opportunities for our faculty and students abound and are virtually limitless in the nation’s capital and surrounding areas. The University is committed to attracting and retaining outstanding and diverse faculty and staff that will enhance our stature of preeminence in our three missions of teaching, scholarship, and full engagement in our community, the state of Maryland, and in the world.
Background Checks
Offers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify you from employment.
Position Summary/Purpose of Position:
The Department of Epidemiology and Biostatistics at the University of Maryland School of Public Health is looking for a post-doctoral fellow to work on a project entitled “Wildfires and Infant Health”. Climate change is increasing the frequency and intensity of wildfires in the United States. Air pollution from wildfires now account for significant proportion of overall air pollution and the contribution of wildfires to air quality will likely increase as they proliferate and other anthropogenic sources decline. Wildfire produced air pollutants are spread across thousands of miles by prevailing winds, potentially increasing of adverse birth outcomes. The post-doctoral fellow, supervised by Drs. Amir Sapkota and Michel Boudreaux will perform statistical analysis linking exposure wildfire related air pollution (developed from satellite observations, ground monitors, and numeric modeling) with adverse birth outcomes including low birthweight, preterm birth, hospital service use, and mortality.
Essential Functions:
Analyses
- Utilize statistical programming languages including but not limited Stata, SAS, R, Python.
- Perform data linkages.
- Perform statistical analysis of large dataset to investigate the associations between exposure to wildfire related air pollution and risk of adverse birth outcome.
- Provide data management, including detailed data cleaning, dataset creation
- Apply methodological expertise in longitudinal analysis and multilevel modeling.
- Implement analyses in close collaboration with and in support of a broader interdisciplinary research team.
- Manage data storage in accordance with IRB and security protocols
Publications and Presentations
- Contribute to publications that summarize study findings.
- Help draft manuscript, prepare tables and figures based on findings, prepare bibliographies.
- Assist in preparing and submitting manuscripts for publication and responding to comments from reviewers and editors.
- Draft abstracts for submission to local, state, and national professional society meetings and other conferences.
- Develop project-related presentation materials
- Initiate, modify, and manage applications to the UMD Committee on Human Research for approval of research studies.
- Participate in the development of new grant proposals, including literature review, identification of databases, and preliminary analyses.
- Be part of an interdisciplinary team of epidemiologists, geographers, and air pollution experts.
Benefits Summary
Top Benefits and Perks:Minimum Qualifications:
Education:
Doctoral degree in Epidemiology or Biostatistics or a related field.
Experience:
Doctoral degree in Epidemiology or Biostatistics or a related field.
Experience:
- Extensive experience with statistical programming and data analysis, including programming in either R, SAS or STATA, and excellent data management skills for designing and constructing large databases. The data are measured at the individual and area-level and also have a time component.
Knowledge, Skills, and Abilities:
- The candidate will also be involved in the writing of manuscripts, so strong writing skills are required.
Preferences:
Preferences:
- Methodological expertise with multilevel, longitudinal data analysis, and GIS mapping. The research project will address issues related to confounding and effect modification.
Additional Information:
- If submitting the optional writing samples, please include published manuscripts.
- The initial appointment will be for one year, with the potential for extension.
Posting Date:
01/11/2024Open Until Filled
YesBest Consideration Date
02/29/2024Physical Demands
Able to take office tasks, ability to sit for extended hours, visual acuity to read data on reports and computer screens, ability to type on keyboard for extended periods.The majority of work is computer-based and is non-labor intensive.
Diversity Statement:
The University of Maryland, College Park, an equal opportunity/affirmative action employer, complies with all applicable federal and state laws and regulations regarding nondiscrimination and affirmative action; all qualified applicants will receive consideration for employment. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, religion, sex, national origin, physical or mental disability, protected veteran status, age, gender identity or expression, sexual orientation, creed, marital status, political affiliation, personal appearance, or on the basis of rights secured by the First Amendment, in all aspects of employment, educational programs and activities, and admissions.
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