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Machine Learning Scientist at UC San Diego - 8+ years, La Jolla, CA, undefined

Role Overview

The CW3E machine learning team is recruiting a scientist to work on the development of artificial intelligence (AI) data-driven weather prediction models. The successful candidate will apply their background and expertise in computational science to develop, support, and execute projects of broad scope and complexity that addresses CW3E's objectives, with a focus on modeling, analyzing, and predicting extreme weather and water events.

Responsibilities

Contribute directly to ongoing developments at CW3E in the domain of AI weather modeling and prediction, including novel architecture and ensemble design.
Develop innovative deep learning-based post-processing methods for quantitative precipitation forecasting (QPF) as well as forecasting other relevant variables, e.g., temperature, integrated water vapor transport (IVT) for the benefit of water management.
Communicate research findings through peer-reviewed journal publications, conference presentations, technical reports, and other publications, as needed.
Give technical presentations to associated research and technology groups and management, and represent the organization at national and international meetings, conferences, and committees.
Support proposal development and contribute to ongoing efforts on the strategic growth of computing platforms and improvement of data management procedures.

Qualifications

Bachelor's degree in a related area and/or equivalent experience. Master's degree or PhD in meteorology, atmospheric sciences, climate science, or a related field preferred.
Experience in implementing machine learning methods in weather/climate research, analysis of dynamical model (e.g., WRF) outputs, and publishing research results.
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.
Thorough skills in analysis and consultation.
Experience in handling numerical weather prediction model simulations, and developing methods for deterministic and probabilistic predictions of hydrometeorological variables.
Research skills to evaluate alternate solutions and develop recommendations. This includes proposing new analyses, new conceptual ideas, or new workflow recommendations.
Experience using common machine learning software (Tensorflow, Keras, PyTorch, Scikit-Learn, etc.) on cloud computing environments (AWS, Azure, etc.).
Knowledge of operational forecasting models and products from NOAA and ECMWF.
Knowledge of observational and reanalysis data sets relevant to US West coast meteorology and climate.
Thorough knowledge of research function. In-depth experience as an independent researcher.
Skills in project management. Strong time management skills. Demonstrated ability to prioritize tasks and meet deadlines.
Skills to communicate complex information clearly and concisely, both verbally and in writing. Skills in scientific writing for peer-reviewed journal publications, scientific graphical representation, and experience presenting at scientific conferences (oral and poster presentations).
Excellent interpersonal skills, including thoughtfulness, diplomacy, and flexibility, with the ability to work independently or within a team framework.

Machine Learning Scientist

UC San Diego

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