CPAESS Associate Scientist IV (Casual)

Visa Sponsored Job:

Relocation Assistance Eligible:

Job Location:

Position Type & Term:

Hourly Rate Range:

$52.45 - $65.56 hourly

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

Application Deadline: This position will be posted until 11:59:59 pm MT on Friday, July 25. Applications will not be accepted past this date.

Required application materials (preferably in PDF Format):

• Resume

• Cover Letter - Please address how your skills and experience meet the needs of this position (for more information, please refer to the Key Responsibilities and Knowledge, Skills, and Abilities sections of this job posting). Candidates should emphasize their experience with:

  • Developing and optimizing data assimilation or reanalysis workflows.

  • Running complex scientific models on high-performance computing (HPC) or cloud environments.

  • Working with large, structured observational datasets, and applying ML methods to emulate or accelerate parts of scientific modeling.

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

Work Location Expectations: This position is open to candidates seeking in-person, hybrid (combination of 3 days in-person and 2 days of remote), or fully remote opportunities. UCAR requires ALL positions to be performed within the U.S., excluding U.S. Territories. CPAESS staff deployed to federal agencies must abide by their respective federal agency requirements concerning remote/flexible work arrangements.

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

Scientific Computing & Data Workflow Development

• Develop workflows on high-performance computing (HPC) and cloud platforms.

• Manage and integrate large-scale observational datasets from the NNJA and WindBorne Global Sounding Balloons.

• Run complex, staged reanalysis processes - from weakly coupled to fully coupled joint-state estimation.

Applied Machine Learning for Scientific Modeling

• Use Machine Learning (ML) emulators to generate ensembles.

• Reduce computational cost through ML-based methods in support of ensemble-based covariance estimation.

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

Education & Experience

• Bachelor's (or equivalent) degree in a scientific discipline pertinent to a NCAR/UCAR scientific program;

• 5+ years of professional experience (preferably as an Associate Scientist III or an equivalent position);

• Demonstrated professional progress leading to the advanced level of knowledge and skills outlined in this job posting.

Desired, but not required:

• Ph.D. in Meteorology/Atmospheric Sciences/Earth Sciences.

• 10+ years of experience in Data Assimilation.

• Experience with integrating new research into the operational systems for data assimilation and ensemble weather prediction.

Knowledge, Skills, and Abilities

• Expert knowledge of scientific principles, research methodologies, and technical specialties relevant to the specific scientific program.

• Advanced skills in designing, executing, and managing complex research strategies and tasks aligned with broad scientific goals.

• Strong ability to communicate scientific concepts, findings, and strategies effectively across diverse formal and informal settings.

Desired, but not required:

• Expertise and demonstrated skill with coupled data assimilation, earth system modeling, JEDI, generating multi-decadal reanalysis data and associated products.

• Knowledge of use of ensembles in weather/climate forecasting and data assimilation.

Applicants are not required to provide age or age-related information and may redact information related to age, date of birth, or dates of attendance at or graduation from an educational institution from any submissions during the initial application process.

At UCAR|NCAR|UCP, you will work alongside a dedicated team of professionals conducting critical research and community outreach to solve complex Earth system science problems including climate change, air pollution, extreme weather, floods, drought, wildfires, and space weather, all with the goal of improving human life and reducing economic loss. Each of us, from scientists to the professionals who support their work, serves the public and a collaborative community of scientists in our mission to understand the complex processes that make up the Earth system, from the ocean floor to the Sun's core.

Flexible Work

At UCAR, we are committed to supporting our mission by giving staff the flexibility to find the schedule and location that works best to maintain their own work-life circumstances and reach their full potential as professionals. Many positions within our organization are eligible for fully on-site, hybrid (three days per week) and/or flexible work hours.

Equal Opportunity Employer

UCAR is committed to providing equal opportunity for all employees and applicants for employment and does not discriminate on the basis of race, age, creed, color, religion, national origin or ancestry, sex, gender, disability, veteran status, genetic information, sexual orientation, gender identity or expression, or pregnancy.Whatever your intersection of identities, you are welcome at UCAR.

Export Control

All positions are required to comply with U.S. export compliance regulations work location requirements regarding access to facilities and research systems.

Visa Wait Times

Please consider the length of visa procurement when applying for this posting, understanding that you will not be able to begin employment until you are able to get a visa and enter the U.S.

Work Location

UCAR requires ALL positions to be performed within the U.S., excluding U.S. Territories.

AI Software

ChatGPT and similar AI software are powerful tools that are changing theway society receives, processes, and leverages information promptly. While we acknowledge its benefits and do not restrict leveraging it with job applications, we highly encourage a majority of the applicant material to be original work.