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Physics Informed Machine Learning Jobs (NOW HIRING)

Direct experience with robotics, autonomous systems, industrial systems, physics-informed machine learning, reinforcement learning, control systems, simulation, digital twins, or real-world telemetry.

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

As of Jun 24, 2026, the average hourly pay for physics informed machine learning in the United States is $20.06, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $25.48 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.

More about Physics Informed Machine Learning jobs
What cities are hiring for Physics Informed Machine Learning jobs? Cities with the most Physics Informed Machine Learning job openings:
What states have the most Physics Informed Machine Learning jobs? States with the most job openings for Physics Informed Machine Learning jobs include:
Infographic showing various Physics Informed Machine Learning job openings in the United States as of June 2026, with employment types broken down into 1% Locum Tenens, 84% Full Time, 11% Part Time, 2% Contract, and 2% Nights. Highlights an 73% Physical, 2% Hybrid, and 25% Remote job distribution, with an average salary of $41,731 per year, or $20.1 per hour.
Internship - Multi-modal sensor fusion for predictive maintenance

Internship - Multi-modal sensor fusion for predictive maintenance

Mitsubishi Electric Research Laboratories

Cambridge, MA

$18.25 - $23.75/hr

Other

Medical

Posted 18 days ago


Job description

Mitsubishi Electric Research Laboratories (MERL) is seeking a self-motivated Ph.D. candidate in Computer Science, Electrical Engineering, or a related field for a 3-month internship focused on developing advanced machine learning algorithms to fuse multi-modal time sequence data for electric machine condition monitoring and predictive maintenance. The ideal candidate will have a strong background in machine learning and signal processing with a proven publication record. Experience in time-sequence analysis, multimodal sensor fusion, or physics-informed machine learning is preferred. Knowledge of electric machines is a plus. The intern will collaborate with MERL researchers to design and develop novel algorithms, prepare technical reports, and contribute to manuscripts for top-tier scientific publications. This position requires onsite work at MERL, with a flexible start date.

Required Specific Experience

  • Experience with multi-modal sensor fusion.

The pay range for this internship position will be 6-8K per month.


Mitsubishi Electric Research Labs, Inc. "MERL" provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, MERL complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

MERL expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of MERLs employees to perform their job duties may result in discipline up to and including discharge.

Working at MERL requires full authorization to work in the U.S and access to technology, software and other information that is subject to governmental access control restrictions, due to export controls. Employment is conditioned on continued full authorization to work in the U.S and the availability of government authorization for the release of these items, which might include without limitation, obtaining an export license or other documentation. MERL may delay commencement of employment, rescind an offer of employment, terminate employment, and/or modify job responsibilities, compensation, benefits, and/or access to MERL facilities and information systems, as MERL deems appropriate, to ensure practical compliance with applicable employment law and government access control restrictions.

In addition to base pay, interns receive a relocation stipend, covered travel to and from MERL, and a monthly Charlie Card for local commuting. Interns are invited to participate in weekly social gatherings and professional development opportunities, including research talks by both internal and external speakers. Interns who meet the 90-day waiting period are also eligible for health insurance coverage. MERL provides immigration support for qualified candidates as needed. Employment is considered at-will, and the Company reserves the right to modify base salary or any other compensation program at any time, including for reasons related to individual performance, departmental or Company performance, and market conditions.