Machine Learning Scientist

Website University of California, San Diego

The scientist will apply their background and expertise in machine learning or computational science to develop, support, and execute projects of broad scope and complexity that addresses CW3E’s objectives. A particular emphasis will be on the application of machine learning (ML) and artificial intelligence methods to weather, subseasonal-to-seasonal (S2S) scale research, and model interpretability. The successful candidate will develop novel methods for precipitation estimation and prediction (as well as other relevant variables, e.g., integrated water vapor transport) for the benefit of water management. The position will lead and contribute reports and peer-reviewed publications as needed, including analyses, diagnostics, figures, and text.

In addition, the position will contribute to ongoing efforts on the strategic growth of computing platforms and resources, improvement of data management procedures, and development of decision support tools.


  • Thorough knowledge of research function. In-depth experience as an independent researcher.
  • Thorough skills associated with statistical analysis and systems programming. Strong experience in scientific programming, working in a Unix environment, and with scripting languages such as Python, R, or Matlab is highly desirable.
    Experience using common machine learning software (Tensorflow, Keras, PyTorch, Scikit-Learn, etc.) on cloud computing environments (AWS, Azure, etc.).
  • Thorough skills in analysis and consultation. Knowledge on how to evaluate numerical weather prediction model performance for both deterministic and probabilistic predictions.
  • Skills to communicate complex information clearly and concisely, verbally and in writing. Skills in scientific graphical representation, scientific writing, and experience presenting at scientific conferences (poster and oral presentations).
  • Skills in project management. Strong time management skills. Demonstrated ability to prioritize tasks and meet deadlines.
  • Research skills at a level to evaluate alternate solutions and develop recommendations. This includes proposing new analyses, new conceptual ideas, or new workflow recommendations.
  • Experience in implementing ML methods in weather/climate research, analysis of dynamical model (e.g., WRF) outputs, and publishing research results.
  • Excellent interpersonal skills, including thoughtfulness, diplomacy and flexibility with the ability to work independently or within a
    team framework in conjunction with principles of community with staff, faculty, researchers, and students.
  • Knowledge of operational forecasting models and products. Knowledge of observational and reanalysis data sets as applied to US West coast meteorology and climate.


Job offer is contingent upon satisfactory clearance based on Background Check results.

The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, age, protected veteran status, gender identity or sexual orientation. For the complete University of California nondiscrimination and affirmative action policy see:

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