Jr Specialist NEX in Mechanical Engineering
Job
University of California - Riverside
Riverside, CA (In Person)
$56,597 Salary, Full-Time
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Job Description
Jr Specialist NEX in Mechanical Engineering University of California
- Riverside $26.35
- $28.07 United States, California, Riverside 900 University Avenue (Show on map) Apr 14, 2026 Position overview Position title: Junior Specialist NEX Salary range: $26.35
- $28.
Application Window Open date:
April 13, 2026 Next review date: Sunday, Apr 26, 2026 at 11:59pm (Pacific Time) Apply by this date to ensure full consideration by the committee.Final date:
Tuesday, Jun 30, 2026 at 11:59pm (Pacific Time) Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled. Position description 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 datasetSoft 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 dataPreferred 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.
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 Qualifications Basic qualifications (required at time of application)
- Applicants must hold a Bachelor's degree in Computer Science, Data Science, Physics, Environmental Science, or a related quantitative field.
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 RequirementsProgramming:
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 datasetSoft 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 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.
- Your most recently updated C.V. Cover Letter
- Please include your research area(s) and specialization. Letter of Reccomendation
- You may provide up to three letters of reference.
Apply link:
https://aprecruit.ucr.edu/JPF02248 Help contact: maricelg@ucr.edu About UC Riverside The University of California, Riverside is a world-class research university with an exceptionally diverse undergraduate student body. UCR is a member institution of the American Association of Universities (AAU) and the Alliance of Hispanic Serving Research Universities (HSRU). A commitment to the UCR mission (https://apro.ucr.edu/mission-statement) is a preferred qualification. We seek to hire scholars who will both advance our research directions and effectively educate our undergraduate and graduate students, while also engaging with University and Professional service activities. Research and teaching statements that are included with application materials are opportunities for candidates to share knowledge, experience, and goals that support the mission of UCR. For more information on UC's criteria for successful faculty, refer to the Academic Personnel Manual (APM) 210- Criteria for Appointment, Promotion, and Appraisal (https://www.
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