The Postdoctoral Research Fellow is a two-year position with the potential to renew for a third year. This is a synthesis postdoctoral program focused on using current, established and collected datasets to further develop the organization?s data-driven approach to decision making as it relates to improving urban tree growth and longevity. The Fellow will help to analyze data and write scientific papers in order to further the work of the organization, city and field of urban forestry. The Fellow will transform information and data into documents, reports, and similar products that tell a compelling story and further define the urban tree growth and longevity in Washington D.C. and the Mid-Atlantic region.
The following essential functions are representative of the Fellow including, but not limited to:
- Refines and statistically analyzes data, ensuring accuracy and security
- Collaborates with team members to connect, understand, and synthesize existing datasets, data sources outside of the organization and geospatial data
- Co-authors and writes peer-reviewed scientific publications
- Conducts work requiring judgment in the evaluation, selection and adaptation/modification of standard techniques, procedures and criteria
- Uses a wide application of complex principles, theories and concepts in the fields of urban forestry and urban ecology
- Connects people to trees
- Other duties as assigned
The incumbent will not have any direct reports.
Position Type/Expected Hours of Work
This is an exempt position, 40-hours a week.
- Applicants must complete all requirements for their Ph.D. by the start date. Applicants may hold a doctoral degree in any natural, physical, or social science discipline. To be eligible for the program, candidates must have received their doctoral degree within four years prior to the start of the fellowship appointment
- Knowledge and proficiency in statistics including a statistical program
- Excellent time management
- Thoughtful, organized, highly collaborative with great attention to detail
- Demonstrated success working in a team environment; both internally and externally
- Excellent written and verbal communication, organizational and interpersonal skills
- Proficiency in Microsoft Office (Word, Excel, PowerPoint, Outlook)
- Working knowledge of the ESRI suite
- Ability to work with and connect multiple large datasets and and use matching methods for causal inference
- Familiarity with quantitative methods for dataset manipulation and analysis
- Familiarity with spatial analysis and remote sensing methods desired
- Knowledge of urban forestry practices