Postdoctoral Research Associate

USNH Employees should apply within Workday through the Jobs Hub app.

The Global Ecology group at the Earth Systems Research Center, University of New Hampshire (UNH), has an immediate opening for a postdoctoral research associate. The successful candidate will apply a dynamic global vegetation model (DGVM) to the conterminous USA and the globe, to explore future projections of vegetation conditions under climate change scenarios. The project is a joint venture with USDA Forest Service, and the study results will inform the Forest Service Resource Planning Act (RPA) Assessment.

The successful candidate is anticipated to have a strong background in modeling and/or global ecology, is highly motivated to produce actionable science, and is ready to lead high‑impact journal publications.

The postdoctoral research associate will be supervised by Dr. Xiao, with additional guidance from and collaboration with other UNH researchers (Dr. Henrique Duarte) and Forest Service researchers (Dr. John Kim). Applications will be considered on a rolling basis until a suitable candidate has been selected. The initial appointment will be for one year, with a possibility to extend depending on performance and funding availability.

• Lead research on the calibration of the DGVM to two spatial extents/resolutions: conterminous USA (CONUS) and the globe.
• Run the calibrated DGVM into the future using CMIP6 future climate projections selected by the FS RPA Assessment.
• Lead manuscript preparation and conference presentations on project findings, with a strong emphasis on publishing high-quality, high‑impact papers.

• A Ph.D. in ecosystem modeling, vegetation modeling, earth system modeling, global ecology, or a related field.

Research and Outreach

Skills:

• Strong research experience in modeling ecosystem processes at local to global scales.
• Experience exploring and manipulating continental to global scale ecological datasets.
• Demonstrated record of publishing in peer‑reviewed journals.
• Demonstrated ability to work effectively in a research team setting.
• Strong interest and motivation in writing high‑impact journal articles.

• Ability to read, understand, explore, and manipulate scientific data files (e.g., netCDF).
• Strong programming skills in a tool that allows effective manipulation of gridded data, such as MATLAB, Python, R, or NCO.
• Ability to read and make limited modifications to C/C++ model source code.
• Ability to use Windows or macOS.
• Ability to run simulations on a high‑performance computing platform running Linux and a job control system such as PBS or SLURM.
• Ability to use various software for composing manuscripts and plotting figures and maps suitable for publication, including GIS.

• Strong written and verbal communication skills.
• Proven ability to meet deadlines.
• Ability to effectively survey and read relevant scientific literature, and collaboratively brainstorm paper‑writing opportunities based on the current project.

Applicants should be prepared to upload the following documents when applying online within the Resume/Cover Letter section of your application:

• Resume/CV
• Cover Letter
• Contact information for three professional references

Applications missing any of the required items may not move forward for consideration. Additional uploaded documents not requested in the position announcement will not be reviewed.

$55,000

The position is supported by external sponsor funding; continued employment depends on the availability of those funds. If the sponsor funding is reduced or discontinued, employment may be modified or terminated in accordance with applicable policies and procedures.

The University System of New Hampshire is an Equal Opportunity/Equal Access employer. The University System is committed to creating an environment that values and supports diversity and inclusiveness across our campus communities and encourages applications from qualified individuals who will help us achieve this mission. The University System prohibits discrimination on the basis of race, color, religion, sex, age, national origin, sexual orientation, gender identity or expression, disability, genetic information, veteran status, or marital status.

Durham

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