"Research Associate"

The School of Forestry at Northern Arizona University seeks a full-time Research Associate to support research efforts on the use of remote sensing data to estimate forest volume and biomass removal in ecological restoration projects. The successful candidate will design and implement workflows for processing aerial LiDAR and other remotely sensed data, perform independent analysis, and contribute to model development and validation across large-scale forest landscapes. The role includes drafting reports, contributing to peer-reviewed publications, mentoring students, and supporting stakeholder engagement across research collaborations.

Responsibilities Include:

• 25% - Research Design & Analysis: Develop and implement research protocols and workflows to process and analyze aerial LiDAR and field data in support of restoration treatment planning (4FRI). Independently perform statistical analysis, modeling, and spatial mapping of estimated forest biomass and volume removal across treatment units. Analyze outputs, quantify uncertainty, and refine methodologies based on evaluation and validation.
• 25% - Tool Development & Data Management: Design or improve existing tools and procedures for data analysis and visualization. Contribute to software/codebase documentation. Ensure data integrity, adherence to research protocols, and compliance with safety and ethical guidelines.
• 25% - Collaboration & Communication: Coordinate with internal and external research partners and funding agencies to ensure quality and relevance of work. Lead or co-author technical reports, peer-reviewed manuscripts, and science delivery products.
• 20% - Mentorship & Training: Mentor graduate and undergraduate students and assist with training on technical tools and methods.
• 5% - Other: Other duties as assigned.

Minimum Qualifications: Master's degree in forestry, ecology, geospatial sciences, biometrics, or a related field, and four or more years of experience conducting and supporting research activities involving geospatial analysis and forest ecology. A combination of related education, experience, and training may be used as an equivalent.

Preferred Qualifications: Ph.D. in landscape ecology, forest biometrics, remote sensing, or a related discipline. Expertise in processing and analyzing LiDAR and other remotely sensed data for forest inventory or ecological applications. Proficiency in machine learning and statistical modeling techniques.

Knowledge, Skills, & Abilities: Knowledge of research principles, forest ecology, remote sensing, and geospatial data processing. Skills in programming or scripting for spatial and statistical analysis (e.g., R, Python). Effective written and oral communication skills. Abilities to conduct complex independent analysis, monitor and evaluate research outcomes, adapt methods, mentor students, and coordinate project tasks.

Compensation: Salary range is $58,882 to $73,434 annually.