Jr Specialist NEX in Mechanical Engineering

Posted: 15-Apr-26

Location: Riverside, California

Type: Full-time

Categories: Academic/Faculty

Internal Number: JPF02248

The Department of Mechanical Engineering at the University of California, Riverside is seeking a motivated Junior AI/ML Specialist to join our environmental research and data science team. Applicants must hold a Bachelor's degree in Computer Science, Data Science, Physics, Environmental Science, or a related quantitative field.

In this role, you will apply machine learning techniques to one of the most challenging problems in fluid dynamics: turbulence prediction within environmental datasets. You will work at the intersection of atmospheric science, optics, and physics, helping us translate complex sensor data and numerical simulations into actionable predictive models for climate and environmental monitoring.

Key Responsibilities:

• Data Pipeline Management: Process and clean large-scale environmental datasets (e.g., LiDAR, satellite imagery, and weather station arrays).
• Model Development: Assist in designing and training neural networks (CNNs, RNNs/LSTMs, or Physics-Informed Neural Networks) to predict turbulent flow and dispersion.
• Feature Engineering: Extract meaningful physical parameters from "noisy" environmental data to improve model accuracy.
• Validation & Testing: Compare ML model outputs against empirical field measurements.
• Collaboration: Work alongside senior faculty and graduate students to understand physical results and correlations and develop understanding into broader environmental forecasting systems.
• Course Development: Work alongside senior faculty and graduate students to develop coursework and course materials related to research outcomes and project efforts.

Technical Requirements:

• Programming: Proficiency in Python and standard ML libraries (PyTorch, TensorFlow, or AutoML).
• Math & Physics: A solid understanding of linear algebra, calculus, and ideally, basic fluid dynamics or atmospheric physics.
• Data Handling: Experience with high-dimensional data formats like NetCDF, HDF5, or GRIB and at least one satellite dataset
• Soft Skills: A "curious tinkerer" mindset--turbulence is chaotic, and finding patterns requires persistence and analytical rigor.
• Writing: Experience preparing figures for presentations, providing results for intermediate reports and preliminary data discussion.
• Data Visualization and Presentation: Excellent didactic skills in data visualization and presentation skills of quantitative data

Preferred Qualifications:

• Experience with academic writing (for example, for a journal publication and responding to comments/criticism)
• Background knowledge of turbulence and environmental measurements (MOST models, Cn2, anemometer, scintillation).
• Familiarity with translating models across different datasets, additive-feature-attribution for interpreting machine-learning models in fluid dynamics and heat-transfer systems.

To apply, candidates should submit a cover letter (including their research area(s) and specialization), a curriculum vitae (CV), and, optionally, up to three letters of reference. Applications must be submitted through UC Riverside Academic Personnel Recruit-Position JPF02248 Application Portal. Full consideration will be given to applications received by April 13, 2026, though the position will remain open until filled. The position is expected to start April 20, 2026. Selected applicants will be invited to interview via Zoom and provide a 15-minute presentation.

For more information about the Department of Mechanical Engineering.

The Jr. Specialist salary range $26.35 -$28.07 an hour. The posted UC salary scales set the minimum pay determined by experience level. UCOP Compensation Salary Scale. For additional information, UCNet RA Union Contract