1

Physics Informed Machine Learning Jobs in Riverside, CA

Develop and validate machine learning models to estimate vehicle loads, drive events, fatigue ... A good understanding of vehicle physics and automotive engineering. * Passion for Rivian's mission ...

Develop and validate machine learning models to estimate vehicle loads, drive events, fatigue ... A good understanding of vehicle physics and automotive engineering. * Passion for Rivian's mission ...

Develop and validate machine learning models to estimate vehicle loads, drive events, fatigue ... A good understanding of vehicle physics and automotive engineering. * Passion for Rivian's mission ...

... Physics or related field. * Minimum of 3 years of industry experience in developing and implementing machine learning and computer vision algorithms and workflows. * Strong programming skills in C/C ...

Stay up to date with the latest advancements in AI, machine learning, and computer vision, evaluate ... Bachelor's or higher degree in Computer Science, Data Science, Electrical Engineering, Physics or ...

Stay up to date with the latest advancements in AI, machine learning, and computer vision, evaluate ... Bachelor's or higher degree in Computer Science, Data Science, Electrical Engineering, Physics or ...

Stay up to date with the latest advancements in AI, machine learning, and computer vision, evaluate ... Bachelor's or higher degree in Computer Science, Data Science, Electrical Engineering, Physics or ...

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

Stay informed about technical trends and actively engage in learning across a broad range of topics, including software architecture, encryption, optimization, machine learning, computer hardware ...

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

CTIO-AI Engineer-Sr Associate

Irvine, CA · On-site

$55K - $187K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

next page

Showing results 1-20

Physics Informed Machine Learning information

See Riverside, CA salary details

$5

$20

$26

How much do physics informed machine learning jobs pay per hour?

As of Jun 6, 2026, the average hourly pay for physics informed machine learning in Riverside, CA is $20.93, according to ZipRecruiter salary data. Most workers in this role earn between $13.03 and $26.59 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Physics Informed Machine Learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are the typical challenges faced by professionals working in Physics Informed Machine Learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What is a Physics Informed Machine Learning job?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are popular job titles related to Physics Informed Machine Learning jobs in Riverside, CA? For Physics Informed Machine Learning jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in Riverside, CA look for? The top searched job categories for Physics Informed Machine Learning jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Physics Informed Machine Learning jobs? Cities near Riverside, CA with the most Physics Informed Machine Learning job openings:
Infographic showing various Physics Informed Machine Learning job openings in Riverside, CA as of May 2026, with employment types broken down into 1% As Needed, 78% Full Time, 16% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $43,536 per year, or $20.9 per hour.
Jr Specialist NEX in Mechanical Engineering

Jr Specialist NEX in Mechanical Engineering

University of California, Riverside

Riverside, CA • On-site

$26.35 - $28.07/hr

Full-time

Posted 24 days ago


University Of California Riverside rating

7.6

Company rating: 7.6 out of 10

Based on 14 frontline employees who took The Breakroom Quiz

240th of 532 rated colleges and universities


Job description

Position overview
Position title: Junior Specialist NEX
Salary range: $26.35 - $28.07
Anticipated start: 04/20/2026
Review timeline: Full consideration will be given to applications received by April 13, 2026, however, the position will remain open until filled. Applications received after the review date will only be considered if the position has not yet been filled.
Application Window
Open date: April 13, 2026
Most recent review date: Sunday, Apr 26, 2026 at 11:59pm (Pacific Time)
Applications received after this date will be reviewed by the search committee if the position has not yet been filled.
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 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
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. Have experience in the following areas:
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
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.
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) as well as the Alliance of Hispanic Serving Research Universities (HSRU). A commitment to the UCR mission is a preferred qualification.
Application Requirements
Document requirements
  • Curriculum Vitae - 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.
    (Optional)

Reference requirements
References are optional. If you are providing reference letters, please combine and upload all reference letters
and include them in the 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.ucop.edu/academic-personnel-programs/_files/apm/apm-210.pdf ).
The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under state or federal law. It is the policy of the University of California to undertake affirmative action and anti-discrimination efforts, consistent with its obligations as a Federal and State contractor.
As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, State, or local government directives may impose additional requirements.
As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.
"Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination, as defined by the employer. A Misconduct Disclosure Survey will be completed through Truescreen, which is the vendor that administers this process for the campus.
For the University of California's Violence and Sexual Harassment Policy please visit:
https://policy.ucop.edu/doc/4000385/SVSH .
For the University of California's Anti-Discrimination Policy for Employees, Students, and Third Parties, please visit: https://policy.ucop.edu/doc/1001004/Anti-Discrimination .
For the University of California's Affirmative Action and Nondiscrimination in Employment Policy, please visit: https://www.ucop.edu/academic-personnel-programs/_files/apm/apm-035.pdf .
Job location
Riverside, CA

What University Of California Riverside employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom