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Forest Carbon Modeling Jobs (NOW HIRING)

University of Arizona

Director, Biosphere 2

Tucson, AZ · On-site

... forest-to address critical questions in ecosystem resilience, water and carbon cycling, and ... Use visitor and retreat operations as platforms for learning-piloting innovative engagement models ...

Enviva

Geospatial Analyst I

Raleigh, NC · On-site

We are the world's largest producer of sustainable wood pellets, which provide a low-carbon ... Bachelor's degree in GIS, geography, forestry, natural resources, environmental science, civil ...

Agupdate

$60K/yr

... to model and scale wetland trace gas fluxes and quantify ecological co-benefits such as ... projects investigating forest and wetland carbon cycling, vegetation structure-function ...

Tamus

Postdoctoral Research Associate

Temple, TX · On-site

Texas A&M Forest Service * Texas A&M Veterinary Medical Diagnostic Laboratory As the nation ... Develop or enhance model algorithms simulating carbon and nutrient budgets under varying manure ...

Tamus

Postdoctoral Research Associate

Temple, TX · On-site +1

Texas A&M Forest Service * Texas A&M Veterinary Medical Diagnostic Laboratory As the nation ... modeling crop growth and yield, water use, and carbon and nitrogen cycling under a range of ...

Enviva

Geospatial Analyst I

Raleigh, NC · Hybrid

We are the world's largest producer of sustainable wood pellets, providing biogenic carbon ... Bachelor's degree in GIS, geography, forestry, natural resources, environmental science, civil ...

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Forest Carbon Modeling information

See salary details

$28.5K

$106.7K

$147.5K

How much do forest carbon modeling jobs pay per year?

As of Sep 13, 2026, the average yearly pay for forest carbon modeling in the United States is $106,690.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,500.00 and $115,000.00 per year, depending on experience, location, and employer.

What is forest carbon modeling?

Forest carbon modeling is the process of using mathematical and computational tools to estimate how much carbon is stored in forests and how it changes over time. These models help scientists and policymakers understand the role forests play in absorbing carbon dioxide from the atmosphere, which is important for addressing climate change. Forest carbon modeling considers factors like tree growth, species composition, soil carbon, disturbances (such as fires), and management practices. The results are used for carbon accounting, conservation planning, and developing carbon offset projects.

What are some common challenges faced by professionals working in forest carbon modeling, and how can they be addressed?

Professionals in forest carbon modeling often encounter challenges such as dealing with incomplete or inconsistent data, integrating diverse data sources (e.g., satellite imagery, field measurements), and keeping up with rapidly evolving modeling tools and methodologies. Staying updated with the latest research, collaborating closely with field ecologists, GIS specialists, and remote sensing experts, and participating in interdisciplinary teams can help overcome these obstacles. Additionally, ongoing training and engagement with professional networks support continuous learning and effective problem-solving in this dynamic field.

What are the key skills and qualifications needed to thrive as a forest carbon modeler, and why are they important?

To thrive as a Forest Carbon Modeler, you need a strong background in forestry, ecology, environmental science, or a related field, often supported by an advanced degree. Proficiency with modeling software (such as CO2FIX, CBM-CFS3, or LANDIS-II), GIS tools, programming languages (like R or Python), and experience with remote sensing data are typically required. Analytical thinking, attention to detail, and effective communication are essential soft skills for interpreting data and collaborating with multidisciplinary teams. These competencies are crucial for producing accurate carbon stock assessments, informing climate policy, and supporting sustainable forest management.

What is the difference between Forest Carbon Modeling vs Forest Data Analyst?

AspectForest Carbon ModelingForest Data Analyst
Required CredentialsEnvironmental science, GIS, modeling certificationsData analysis, statistics, GIS certifications
Work EnvironmentFieldwork, modeling, software-based analysisData management, reporting, software tools
Industry UsageClimate projects, carbon offset programsForest management, research, conservation

Forest Carbon Modeling focuses on creating predictive models of carbon sequestration in forests, often involving complex software and environmental data. Forest Data Analysts interpret and manage forest-related data to support decision-making. While both roles require GIS and environmental knowledge, modeling emphasizes predictive analysis, whereas data analysis centers on data management and reporting.

What other helpful pages are available for Forest Carbon Modeling?

Other pages related to Forest Carbon Modeling:

Infographic showing various Forest Carbon Modeling job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $106,690 per year, or $51.3 per hour.

TES Research Associate

Auburn University, AL • On-site

Auburn University
Colleges, Universities, and Professional Schools • 1 - 5K employees
Learn more about Auburn Universityexternal

$20/hr

Full-time

Re-posted 4 days ago

Key responsibilities

  • Develop and implement machine learning and deep learning models to analyze forestry, physiological, and ecological datasets

  • Model plant growth, carbon allocation, stress response, and ecosystem productivity using AI-based approaches

  • Integrate multi-modal datasets and support data preprocessing, cleaning, normalization, and database organization

Auburn University rating

6.5

Company rating: 6.5 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

Job description

Overview
The TES Research Associate will work with scientists and students under the supervision of Dr. Chen - to support research related to AI-driven modeling of forestry systems, plant physiological processes, and ecological traits. The position will focus on developing computational models integrating multi-source datasets, including remote sensing, field measurements, environmental variables, and biological trait data.
Temporary Employment Services (TES), a unit of the Auburn University Department of Human Resources, is an in-house support center established to meet the temporary employment needs of the university. TES provides qualified and dedicated temporary employees in a wide variety of occupations to meet the staffing needs throughout the campus. Temporary employees are hired for a variety of reasons with the most common being:
  • Assistance in the place of a regular employee who is absent for a specified period of time
  • Additional assistance during periods of abnormal or peak workloads
  • Assistance with special projects
  • Seasonal work
  • Emergencies

If you are looking for an employment opportunity, TES is a great way to showcase your professional skills and assist Auburn University while gaining valuable work experience within higher education.
AU students are not eligible for TES.
Responsibilities
  • Developing and implementing machine learning and deep learning models to analyze forestry, physiological, and ecological datasets
  • Modeling plant growth, carbon allocation, stress response (e.g., drought, salinity), and ecosystem productivity using AI-based approaches
  • Integrating multi-modal datasets (remote sensing, UAV/drone imagery, field inventory data, soil and climate parameters, and genomic/trait data)
  • Conducting statistical modeling, feature selection, and predictive analytics for forest health, resilience, and biomass estimation
  • Supporting data preprocessing, cleaning, normalization, and database organization
  • Assisting in the preparation of research reports, manuscripts, and grant proposals
  • This position will provide hands-on experience in applying artificial intelligence and computational modeling techniques to complex biological and ecological systems, with applications in forest productivity, climate resilience, and sustainable resource management.

Qualifications
Master's degree in Computer Science, Artificial Intelligence, Data Science, or a closely related field.
Minimum Knowledge, Skills, and Abilities
    • Experience in machine learning, deep learning, and statistical modeling
    • Strong programming skills (e.g., Python, R, TensorFlow/PyTorch)
    • Experience handling large-scale ecological, biological, or remote sensing datasets
    • Strong scientific writing and communication skills
    • Interest in interdisciplinary research in forestry, plant physiology, and ecosystem science

Why Work at Auburn?
  • Life-Changing Impact: Our work changes lives through research, instruction, and outreach, making a lasting impact on our students, our communities, and the world.
  • Culture of Excellence: We are committed to leveraging our strengths, resources, collaboration, and innovation as a top employer in higher education.
  • We're Here for You: Auburn offers generous benefits, educational opportunities, and a culture of support and work/life balance.
  • Sweet Home Alabama: The Auburn/Opelika area offers southern charm, vibrant downtown scenes, top-ranked schools, and easy access to Atlanta, Birmingham, and the Gulf of Mexico beaches.
  • A Place for Everyone: Auburn is committed to fostering an environment where all faculty, staff, and students are welcomed, valued, respected, and engaged.
  • Ready to lead and shape the future of higher education? Apply today! War Eagle!

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