Postdoctoral Research Associate Position at Pacific Northwest National Laboratory (PNNL), USA (2026)
This opportunity is designed for researchers interested in applying advanced computational methods and machine learning to complex scientific challenges involving energy, water, land use, and environmental change. The successful candidate will contribute to research integrating Earth system model outputs with human system models, develop simulation scenarios, quantify uncertainty, and publish scientific findings in peer-reviewed journals.
The position offers a stated annual salary range of $69,000 to $119,100, along with a collaborative research environment and opportunities to work with multidisciplinary teams across PNNL, other national laboratories, and universities.
Position Overview
| Category | Details |
|---|---|
| Position Title | Post Doctorate RA – Human & Earth System Science |
| Institution | Pacific Northwest National Laboratory (PNNL) |
| Location | College Park, Maryland, USA |
| Research Area | Machine Learning, Deep Learning, Human-Earth System Modeling |
| Position Type | Temporary, full-time |
| Job ID | 12634 |
| Annual Salary | $69,000–$119,100 USD |
| Application Deadline | November 16, 2026, at 4:00 PM PST |
| Minimum Qualification | PhD obtained within the past five years or expected within the next eight months |
| Official Application Portal | PNNL Careers website |
About Pacific Northwest National Laboratory
Pacific Northwest National Laboratory is a major scientific research institution managed and operated by Battelle for the U.S. Department of Energy. The laboratory brings together researchers from multiple scientific and technical disciplines to address challenges in energy, environmental resilience, national security, and fundamental science.
The position is associated with PNNL’s Integrated Discovery Sciences Directorate, which conducts research across biology, chemistry, Earth and environmental sciences, materials science, advanced computing, artificial intelligence, mathematics, and related fields.
Researchers in this environment work across disciplinary boundaries to develop scientific capabilities, improve understanding of complex systems, and support discoveries with practical applications.
Research Project and Objectives
The postdoctoral researcher will work at the intersection of machine learning, human-Earth system modeling, and advanced model development. A central component of the research involves using the Global Change Analysis Model (GCAM) to investigate how human and Earth system drivers influence energy, water, and land systems.
The project will combine large collections of Earth system model outputs with human system modeling approaches. It will also explore the use of emerging Super Intelligence (SI)-enabled methods to improve scientific model development and analysis.
The work aligns with the U.S. Department of Energy’s Genesis Mission, which aims to advance an integrated, SI-driven scientific platform to accelerate discovery in energy, national security, and technology.
Key Responsibilities
The selected candidate will contribute to several interconnected research activities.
1. Process Earth System Model Outputs
The researcher will process and analyze large ensembles of Earth system model outputs, including data from:
Energy Exascale Earth System Model (E3SM).
Coupled Model Intercomparison Project datasets, including CMIP6 and CMIP7 outputs available through the Earth System Grid Federation (ESGF).
These datasets will support the development and analysis of integrated human-Earth system models.
2. Develop Machine Learning and Deep Learning Models
The postdoctoral researcher will design and develop machine learning and deep learning methods to connect Earth system model outputs with human system models. The goal is to support integrated scientific analysis and improve the modeling of interactions between environmental processes and human activities.
3. Conduct GCAM Scenario Analysis
The successful applicant will develop scenarios and generate large ensembles of Global Change Analysis Model simulations. These simulations will help investigate the impacts of changing human and Earth system drivers, including extreme weather events.
4. Quantify Impacts on Energy, Water, and Land Systems
The researcher will analyze simulation results to assess how changes in environmental and human drivers affect energy demand and supply, water systems, and land use.
The work will contribute to a more integrated understanding of complex interactions across human and natural systems.
5. Publish Scientific Research
The candidate will be expected to lead multiple peer-reviewed publications based on the research. Strong scientific writing, data analysis, and communication skills will be important for sharing findings with the research community.
6. Collaborate Across Research Disciplines
The role provides opportunities to work with multidisciplinary research teams at PNNL and collaborate with scientists from other national laboratories and universities.
The researcher will also be encouraged to explore emerging SI-based solutions for scientific model development.
Eligibility Criteria
Applicants should review the minimum and preferred qualifications carefully before applying.
Minimum Qualifications
Candidates must meet the following requirements:
Have received a PhD from an accredited college or university within the past five years (60 months), or expect to receive the degree within the next eight months.
Have an academic background in computational science, engineering, applied mathematics, physical sciences, economics, hydrology, or a related field.
Preferred Qualifications
The following skills and experiences are particularly relevant:
Strong written and verbal communication skills.
Substantial programming experience.
Previous graduate-level coursework in statistics.
Experience publishing, or demonstrated ability to publish, research in peer-reviewed journals.
Ability to work independently and collaborate effectively in a multidisciplinary team.
Experience with Python, R, and/or C++.
A strong background in machine learning and deep learning methodologies.
Interest in applying evolving Super Intelligence methodologies to scientific research and modeling.
Applicants with experience in scientific computing, data-intensive research, environmental modeling, or integrated assessment modeling may find the research particularly relevant to their interests. However, the official posting does not specify that experience with every listed model or programming language is mandatory.
Salary and Benefits
Annual Salary
The advertised salary range for this position is:
Minimum: $69,000 per year.
Maximum: $119,100 per year.
The final salary within this range depends on relevant job-related skills, qualifications, and experience. The advertised range should not be interpreted as a guarantee that every successful applicant will receive the maximum amount.
Employee Benefits
PNNL describes a range of benefits for eligible employees. These may include:
Medical, dental, and vision insurance.
Telehealth services and mental health benefits.
Wellness coaching and employee assistance programs.
Health savings and flexible spending accounts.
Basic life and disability insurance.
Tuition assistance.
Relocation assistance, where applicable.
Backup childcare.
Supplemental parental bonding leave.
Adoption, surrogacy, and fertility support.
A company-funded pension plan and access to a 401(k) savings plan with company match, subject to eligibility and applicable employee categories.
Accrual of up to 120 vacation hours annually and up to ten paid holidays.
Flexible work schedules.
PNNL notes that benefits depend on eligibility and that some benefits, including certain retirement benefits, have employee-category exclusions. Applicants should confirm the specific terms that apply to this Research Associate position.
Important Employment and Eligibility Considerations
Because PNNL is a U.S. national laboratory, applicants should be aware of additional employment requirements.
Security credentialing: New employees must satisfy applicable federal credentialing and background-investigation requirements. Foreign-national candidates who have not resided in the United States for three consecutive years may need a different site-specific federal risk determination under the conditions described in the posting.
Drug testing: The laboratory states that candidates who receive an offer must pass a pre-employment drug test and that federal rules concerning controlled substances apply.
Government affiliations: The posting identifies restrictions concerning affiliations with the governments of certain countries designated by the Department of Energy as countries of risk. Applicants to whom this may apply should review the official requirements carefully.
These provisions are part of the employment conditions described by PNNL and may affect individual applicants differently.
How to Apply
Interested candidates should apply through the official PNNL Careers portal and review the complete vacancy announcement before submitting an application.
Official Application Link
APPLY HERE: PNNL careers website
Application Deadline
The application deadline listed in the vacancy announcement is November 16, 2026, at 4:00 PM Pacific Standard Time (PST).
Applicants should submit their materials before the deadline and confirm the time displayed on the official application portal.
Frequently Asked Questions (FAQs)
1. What is the position offered at PNNL?
Pacific Northwest National Laboratory is recruiting for a Post Doctorate Research Associate position in Human & Earth System Science, focused on machine learning, deep learning, and integrated human-Earth system modeling.
2. Where is the position located?
The position is listed in College Park, Maryland, USA.
3. What is the salary for this postdoctoral position?
The advertised annual salary range is $69,000 to $119,100 USD. Actual compensation depends on relevant qualifications, skills, and experience.
4. Who is eligible to apply?
Candidates must have received a PhD within the past five years or expect to receive one within the next eight months. Relevant backgrounds include computational science, engineering, applied mathematics, physical sciences, economics, hydrology, and related fields.
5. Is programming experience required?
Substantial programming experience is listed among the preferred qualifications. Python, R, and C++ are identified as particularly useful languages. The role also requires a strong background in machine learning and deep learning methodologies.
6. What research will the successful candidate conduct?
The researcher will process large Earth system model datasets, develop machine learning and deep learning models, generate GCAM simulation scenarios, and analyze the effects of human and environmental drivers on energy, water, and land systems.
7. Will the researcher be expected to publish papers?
Yes. The successful applicant is expected to lead multiple peer-reviewed publications arising from the research.
8. What is the application deadline?
The deadline is November 16, 2026, at 4:00 PM PST, according to the supplied vacancy announcement.
Final Thoughts
The Post Doctorate Research Associate position in Human & Earth System Science at Pacific Northwest National Laboratory offers an opportunity for PhD researchers to apply machine learning and deep learning to important scientific questions involving climate and Earth system modeling, human activity, energy, water, and land use.
The combination of large-scale model analysis, GCAM simulations, multidisciplinary collaboration, and peer-reviewed research may appeal to candidates with strong computational and quantitative backgrounds. Eligible researchers interested in scientific machine learning and integrated environmental modeling should review the official vacancy announcement and submit their applications before the November 16, 2026 deadline.
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