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Full Time Climate Modeling Jobs (NOW HIRING)

The Pennsylvania State University

... models, perturbed-parameter ensembles, or other physically grounded approaches to understand ... BENEFITS Penn State provides a competitive benefits package for full-time employees designed to ...

Climate United FUND

Investment Officer

Bethesda, MD · On-site

Climate United Fund, a 501(c)(3) nonprofit ("Climate United"), is seeking several full-time ... Lead financial modeling and risk assessment activities. * Lead portfolio servicing and day-to-day ...

Climate United FUND

Investment Officer

Bethesda, MD · On-site +1

Climate United Fund, a 501(c)(3) nonprofit ("Climate United"), is seeking several full-time ... Lead financial modeling and risk assessment activities. * Lead portfolio servicing and day-to-day ...

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Full Time Climate Modeling information

What is full time climate modeling?

Full time climate modeling jobs involve using computer simulations and mathematical models to study and predict climate patterns and changes. Professionals in these roles analyze data related to the atmosphere, oceans, and land to understand how climate systems interact and how they might change over time. These jobs are typically found in research institutions, government agencies, and environmental organizations. They often require strong analytical skills, knowledge of programming, and expertise in atmospheric or environmental science. The goal is to provide insights that help society prepare for and respond to climate change.

What are the key skills and qualifications needed to thrive as a full time climate modeler?

To thrive as a Full Time Climate Modeler, you need strong quantitative skills, expertise in atmospheric or earth sciences, and an advanced degree (often a master's or Ph.D.) in a related field. Proficiency with programming languages like Python or Fortran, experience using climate modeling software (e.g., GCMs), and familiarity with data analysis tools such as MATLAB or R are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you interpret complex data and present findings to diverse audiences. These capabilities are crucial for producing reliable models and actionable insights that drive scientific understanding and inform policy or business decisions related to climate change.

What are some common challenges faced by professionals in full time climate modeling roles, and how can they be addressed?

Professionals in full-time climate modeling often encounter challenges such as managing large datasets, ensuring model accuracy, and keeping up with evolving computational methods. Collaborating with interdisciplinary teams—including atmospheric scientists, data analysts, and software engineers—is essential to address these challenges effectively. Staying updated with the latest research, regularly validating models, and leveraging high-performance computing resources can help professionals overcome obstacles and deliver reliable climate projections.

What is the difference between Full Time Climate Modeling vs Full Time Climate Data Analysis?

AspectFull Time Climate ModelingFull Time Climate Data Analysis
Required CredentialsDegree in Climate Science, Meteorology, or related field; experience with modeling softwareDegree in Data Science, Statistics, or related; proficiency in data analysis tools
Work EnvironmentResearch labs, universities, government agenciesResearch institutions, environmental organizations, government agencies
Industry UsageDeveloping climate models, simulations, scenario projectionsAnalyzing climate data sets, interpreting results, reporting findings

Full Time Climate Modeling focuses on creating and running climate simulations to predict future conditions, while Full Time Climate Data Analysis emphasizes examining existing climate data to identify trends and insights. Both roles require strong scientific backgrounds but differ in their core tasks and tools used.

Do full time climate modeling jobs pay well?

Full time climate modeling jobs typically offer competitive salaries that vary based on experience, education, and location. Professionals with advanced degrees and skills in programming, data analysis, and climate science tend to earn higher wages, with many positions providing benefits and opportunities for advancement.
More about Full Time Climate Modeling jobs

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Cities with the most Full Time Climate Modeling job openings:

What are the most commonly searched types of Climate Modeling jobs?

The most popular types of Climate Modeling jobs are:

What job categories do people searching Full Time Climate Modeling jobs look for?

The top searched job categories for Full Time Climate Modeling jobs are:

Full Time Climate Modeling jobs near you
Infographic showing various Full Time Climate Modeling job openings in the United States as of August 2026, with employment types broken down into 86% Full Time, 11% Part Time, and 3% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.

Postdoctoral Research Position in AI for Healthy Climate Adaptation

Harvard University

Cambridge, MA • On-site

$75K/yr

Full-time

Re-posted 11 days ago

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Company rating: 8.5 out of 10

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Job description

Position
Details
Title
Postdoctoral Research Position in AI for Healthy Climate Adaptation
School
Harvard T.H. Chan School of Public Health
Department/Area
Biostatistics
Position Description
Position Description
The National Studies on Air Pollution and Health (NSAPH) group, led by Prof. Francesca Dominici, invites applications for a full-time Postdoctoral Research Fellow to join a massive research effort developing next-generation AI methods for healthy climate adaptation. The position will focus on building and evaluating foundation models for large-scale spatiotemporal health and environmental data. Our team leverages nationwide Medicare claims data for older adults in the United States, linked with rich contextual information, including census, weather, and air pollution data. The overarching goal is to develop domain-specific foundation models that support tasks such as forecasting, interpolation/extrapolation, downscaling, and "what-if" scenario analysis relevant to climate-related health risks and adaptation strategies.
Duties and Responsibilities
  • Design, implement, and evaluate deep learning models for spatiotemporal data, with an emphasis on medium-scale foundation models.
  • Leverage model embeddings in causal inference pipelines for health effects and adaptation policy evaluation.
  • Work with large, high-dimensional datasets (Medicare claims, census, weather, pollution, and related data), including data preprocessing, integration, and harmonization.
  • Lead and contribute to manuscripts for high-impact journals and conferences (e.g., Nature-like journals or top CS conferences).
  • Present findings in internal meetings and at national/international conferences.
  • Collaborate with an interdisciplinary team of biostatisticians, computer scientists, and climate scientists.
  • Contribute to open-source code, reproducible research workflows, and, where possible, public tools or model artifacts.

Basic Qualifications
  • PhD (completed or near completion) in one of the following or a closely related field:
    • Computer Science
    • Statistics / Biostatistics
    • Applied Mathematics
    • Data Science
  • Demonstrated expertise in modern machine learning, including at least one of the following:
    • Deep learning (e.g., transformers, sequence models, representation learning)
    • Spatiotemporal modeling or geospatial/temporal data analysis
    • Medium-to-Large-scale foundation models pretraining/fine-tuning paradigms
  • Strong programming skills in Python and experience with PyTorch, required to have experience developing code with a team through collaborative version control
  • Experience working with large datasets and cloud computing environments.
  • Solid background in statistical modeling and inference
  • Excellent written and oral communication skills, with a track record of peer-reviewed publications commensurate with career stage.

Additional Qualifications
Prior experience with one or more of:
  • Health claims data, EHRs, or other large-scale health/administrative datasets
  • Environmental, climate, or air pollution exposure data
  • Causal inference methods
  • Uncertainty quantification and model calibration for decision-making
  • Familiarity with interdisciplinary work at the interface of climate, environment, and health.

Special Instructions
Please submit the following materials:
  • Cover letter describing your research interests, relevant experience, and fit for this position.
  • Curriculum vitae including a list of publications.
  • One to three representative publications or preprints.
  • Names and contact information for 2-3 references.

Contact Information
Catherine Adcock
Contact Email
catherine_adcock@harvard.edu
Salary Range
$75,000
Minimum Number of References Required
2
Maximum Number of References Allowed
3
Keywords
biostatistics; artificial intelligence; climate science

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