CIWRO Research Associate – Tornado Deep Learning Radar Applications


The Cooperative Institute for Severe and High-Impact Weather Research and Operations (CIWRO), formerly CIMMS, at the University of Oklahoma currently is seeking a research associate to collaborate with scientists in the National Severe Storms Laboratory’s (NSSL) Warning Research & Development Division on the development of machine learning applications for short-term prediction of severe thunderstorms and their attendant hazards. The incumbent will use their expertise to apply machine learning, including deep learning, on radar-based data sets to investigate severe storms and produce new algorithms to improve severe weather warning guidance and understanding of tornadic thunderstorms. The position will primarily focus on the needs and goals of NOAA’s Tornado Warning Improvement and Extension Program (TWIEP).

The duties of the position are:

  1. Development of deep learning models operating on weather data images to

    investigate tornadic thunderstorms and improve the short-term prediction of


  2. Investigating novel techniques to parse radar data images and classify

    thunderstorm structures to investigate tornadic thunderstorms and their structures;

  3. Attend meetings and professional conferences to present research results and

    interact with collaborators and users;

  4. Meet with collaborators and provide regular summaries of work accomplished;
  5. Review technical and professional publications and attend seminars to stay

    abreast of current developments in meteorological, remote sensing, and computing and/or machine learning science.

The minimum qualifications for the position are:

  1. Masters Degree in Computer Science or Data Science and Analytics or related areas;
  2. ExperiencewithscientificprogrammingonUNIX/Linuxsystemsusingahigh-level language (e.g., C++, Python, Java);
  3. Experience with deep learning software (e.g., Tensorflow, PyTorch);
  4. Experienceusingimagedataindeeplearning.

Applicants should identify expertise with any of the following areas: weather radar data and principles; severe local storms and their attendant hazards; statistics; data science; machine learning; deep learning; image data processing; supercomputing and/or cloud computing environments. Strong oral and written communication skills are needed for

the position, including the ability to present research to various audiences and collaborate on reports and publications.

Normal working hours will be observed except for occasional irregular hours during data collection, warning/forecast experiments, or workshops conducted at remote sites. Supervision will be provided by CIWRO staff. Technical oversight will be provided by CIWRO staff, NSSL scientists, and NSSL management. The incumbent will work under general supervision but is expected to determine action to be taken in handling all but unusual situations. Incumbents in this position are not expected to supervise other employees but may supervise students.

Incumbents will have opportunities to receive training and gain expertise in the latest radar and other remote sensing technology, and, as needed by the position’s technical requirements, technical skills related to programming and machine learning. Incumbents will also have opportunities for career development through resources provided by the University; more information may be found at Development.

The beginning salary will be based on qualifications and experience with University benefits. Information on benefits may be found at The position will be located in Norman, OK ( at the National Weather Center (

To apply for the position, please forward your resume, cover letter and list of three references to:

CIWRO Careers
University of Oklahoma CIWRO
120 David L. Boren Blvd., Suite 2100 Norman, OK 73072-7304
ATTN: Tornado Deep Learning Radar Apps

The University of Oklahoma is an equal opportunity/Affirmative Action employer.

The University of Oklahoma complies with the Federal COVID-19 vaccine requirement for all employees. All current and future employees must provide proof of full vaccination or request an accommodation for exemption from the Federal requirement. For detailed information regarding this requirement, visit

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