Postdoctoral Research Scholar

Essential Job Duties

The Department of Forestry and Environmental Resources has a wide variety of strengths in forestry and natural resources management, policy and economics, environmental science and technology, renewable energy assessment, wildlife and conservation biology, tree improvement, silviculture, forest biotechnology, and international forestry. The Department has over 90 full time faculty and staff, and more than 750 undergraduate and 150 graduate students.

Core duties and responsibilities include:

• Leading and conducting collaborative research on the influence of climate variability on mountainous forest ecosystems as part of the Watershed Science Focus Area.
• Developing integrative analysis/approaches that use field observation of tree ring data (width and carbon and oxygen isotopes), remote sensing data, machine learning, and modelling to investigate forest changes and decline due to perturbations (e.g., warming, drought).
• Co-leading field campaigns for ground data collections in the Rocky Mountains for several days.
• Authoring peer-reviewed conference and journal papers.
• Participating actively in project meetings and workshops.

Seeking a Postdoctoral Research Scholar for an immediate project. Funding is guaranteed for an initial 6 months, with a further 6-month extension contingent upon funding.

Departmental Required Skills

• Demonstrated evidence of strong research and publication skills, and future research productivity.
• Demonstrated quantitative and computational skills including coding skills in at least one of these languages: Python, R.
• Have domain knowledge in a relevant field such as ecology, ecosystem science, ecophysiology, ecohydrology, stable isotope applications, or land-atmosphere interactions.
• The ability to carry out an original research agenda in ecohydrology and tree physiology.

Preferred Experience, Skills, Training/Education

• Research experience in forest science, tree physiology, stable isotopes (13C & 18O), and/or dendrochronology.
• Experience with LiDAR and hyperspectral imaging or other remote sensing.
• Familiarity with libraries, frameworks, or workflow tools that enable data analytics and machine learning.
• Interest in collaborative research, open science, and implementing maintainable and reusable software/data products for broader scientific use.