Job description
This project is a collaborative effort between the Garnas lab at the University of New Hampshire, the Fearer lab at Virginia Tech, and researchers from Purdue University and the United States Forest Service.
Work for this position can be local, either at the University of New Hampshire or at Virginia Tech, or remote within the US, depending on location. The first year of funding comes from the University of New Hampshire. Funding for a second year is available from Virginia Tech, contingent on satisfactory performance in year 1. Relocation is not required to be eligible for a second year of funding.
- PhD degree (in Ecology, Forestry, Natural Resources, Biostatistics, or related field) in hand by the start date, preferably August 2023 or soon thereafter.
- Strong statistical, analytical, and data wrangling skills
- Experience working with large datasets and/or at large spatial scales
- Demonstrated programming ability (i.e., R, Python, or other language; experience with SQL is preferred but not required).
- Evidence of a growing publication record consistent with the candidate’s career stage
- Creativity, flexibility, and a passion for inquiry
- Strong writing and communication skills
- Ability to work both independently and as a team member and leader
The University System of New Hampshire is an Equal Opportunity/Equal Access/Affirmative Action 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.
Instructions for reference providers can be access at: https://support.interfolio.com/m/29600/l/266335-submit-a-letter-of-recommendation-to-interfolio.
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