Position Type:

Term - 6 months or more (Fixed Term)

Visa Sponsored Job:

Yes

Relocation Assistance Eligible:

Yes

Hiring Range:

82,650.00 USD - 82,650.00 USD

*Final salary and rates are based on education, experience, and skills relevant to the role.

Application Closes at 12:00am MST on:

2026-08-11

About the Role

UCAR is excited to announce the job opening for the Mesoscale and Microscale Meteorology (MMM) Postdoctoral Fellow role. This position will contribute to research activities within NCAR’s MMM laboratory related to developing a GPU-compatible and auto-differentiable version of the Model for Prediction Across Scales (MPAS) using a higher-level, interpreted language such as JAX. The MMM Postdoctoral Fellow will interact with NCAR scientists, staff, and other postdoctoral fellows to advance the research over the position’s one-year term, and will be encouraged to present at scientific conferences, publish scientific papers, and pursue professional development activities.

The mission of MMM is to lead and enable research that advances the understanding of weather and to apply this knowledge to benefit society. In support of this mission, MMM strives to produce accurate and effective computational models, data assimilation systems, and representations of unresolved weather model processes from local to global scales. We also conduct theoretically driven social science and interdisciplinary research that connects to the hazardous weather predictability and prediction capabilities. With extensive external contributions, MMM’s efforts have included development of the Weather Research and Forecasting (WRF) model, the Model for Prediction Across Scales (MPAS), and sophisticated codes for cloud-resolving and eddy-resolving simulations. MMM continues to emphasize boundary-layer, turbulence and cloud-microphysics research. Eddy-resolving simulations of mesoscale phenomena such as tropical cyclones, mesoscale convective systems and fronts in the atmosphere and ocean enable research of multi-scale dynamics., i.e., a deeper understanding of interactions across a continuous spectrum of mesoscale and microscale atmospheric motions.

Job Description

Application Deadline: This position will be posted until 11:59pm MT on Tuesday, August 11, 2026. Applications will not be accepted past this date.

Required application materials: 

• Resume - preferably in PDF Format

• Questionnaire - to be completed when submitting your application
  In lieu of a traditional cover letter, answer the following prompts that address the critical skills needed for this position. Your answers will be read and weighed equally to your Resume/CV and should provide specific, detailed, and informative responses based on your direct and previous work experiences. Please keep responses to 1-3 paragraphs per prompt.

  • Summarize your background in the computational simulation of fluid systems, especially the atmosphere. Did you write code? Did you perform numerical analysis of the computational solver? Did you address optimization and scaling of the computations? Did you work with or develop codes that were differentiable? How big were the problems you worked on?

  • Please briefly describe your experience related to the use of GPUs for computational fluid simulations. (See above for possible dimensions your answer might consider.)

  • Suppose you had a year to do unconstrained research related to computational simulations of the atmosphere. What would you do, and why is it interesting?

Background checks are conducted for candidates selected for hire. Learn more.

Work Location Expectations:  This position is open to candidates seeking in-person or hybrid (combination of 3 days in-person and 2 days of remote) opportunities. UCAR requires ALL positions to be performed within the U.S., excluding U.S. Territories. 

What You Will Do

Here is a brief summary of what one would expect to be generally responsible for in this role.

Key Responsibilities

• Conduct independent and collaborative research in machine learning for prediction of the Earth system or its components.

• In collaboration with the PANDA-C team in MMM, develop machine-learning techniques that improve 0-12 h predictions of atmospheric cloud relative existing MPAS-JEDI baseline. These techniques may supplement components of MPAS-JEDI, or use MPAS-JEDI outputs and satellite observations as inputs.

• Prepare research results for publication in peer-reviewed journals. Present results at conferences. Assist with project reporting as needed.

Who We'd Love To Join Our Team

Successful candidates will ensure their application materials speak to the following criteria:
 

Education and Experience:

• Ph.D. degree within the last 5 years or expected within the next 6 months in atmospheric science, computer science, statistics, or a related area.

Knowledge, Skills, and Abilities:

• Advanced knowledge of numerical and computational techniques for fluid dynamics simulations, especially of the atmosphere.

• Advanced skills in developing and deploying computational simulations of physical systems on GPUs.

• Demonstrated ability to work independently and collaboratively as part of a research team.

• Excellent time management and organization skills.

• Demonstrated and effective written and oral communication skills.

Desired, but not required:

• Subgrid parameterizations in computational fluid mechanics.

• Basic knowledge of physical parameterizations used in computational models of the atmosphere, or more generally subgrid parameterizations in computational fluid mechanics.

• Skill in developing efficient, scalable, and maintainable software for the simulation of physical systems.

Preferred Qualifications

Hiring Salary Rate: $82,650

*Final salary and rates are based on education, experience, skills relevant to the role.*

Application Requirements

Questionnaire, Resume/CV

For full consideration, all application materials must be submitted by 12am (MST) at the start of the application deadline. These should highlight how your skills and experiences align with the responsibilities of this position. We recognize that no candidate will meet 100% of the listed qualifications. If you believe your background has prepared you for success in this role, we encourage you to apply.

Supplemental questionnaires are often requested in lieu of a cover letter, where you address critical skills needed for the position. Your answers will be read and weighed equally to your resume and should provide specific, detailed, and informative responses based on your direct and previous work experiences.

Background checks and/or federal screenings are conducted for candidates selected for hire.

Benefits Overview 

UCAR offers a comprehensive benefits package: health insurance, dental, retirement plan, leave plans, tuition assistance, and employee assistance programs:

• Medical, Dental, Vision, and Short & Long Term Disability Insurance
• Generous retirement plan - UCAR contributes of 10% of base salary
• Time Off Plans
  • Minimum 20 days of annual PTO
  • 10 paid holidays
  • 12 weeks of paid parental leave
  • FAMLI Leave 
• Tuition Assistance Program
• Public Service Loan Forgiveness (PSLF) eligible employer

UCAR is an Equal Opportunity Employer and welcomes applications from all individuals. We do not discriminate on the basis of race, age, sex, gender identity, disability, veteran status, or any other characteristic protected by law. Applicants are not required to provide age-related information (like date of birth or graduation dates) in initial submissions.

For sponsored positions: UCAR can sponsor individuals for H-1B status only if they are already in the U.S. in H-1B status or another visa status that allows them to change to H-1B status within the U.S. UCAR is unable to sponsor new H-1B visas for individuals who are outside the U.S. and need to obtain H-1B status through Consular Processing.

While UCAR does not prohibit the use of AI tools in job applications, we strongly recommend that applicants submit primarily original work.

All roles require compliance with U.S. export control regulations and work location requirements. All hybrid staff are expected to work on-site approximately 3 days per week.