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Physics Informed Machine Learning Jobs (NOW HIRING)

Digital Harbor Foundation

Research Scientist

Baltimore, MD · On-site +1

$120K - $150K/yr

Design and implement physics-informed machine learning models to improve predictive accuracy * Quickly learn and apply new tools, datasets, and methods to address evolving project needs * Apply ...

Causal Labs

Machine Learning - Research

San Francisco, CA · On-site

$241K/yr

Strong grasp of machine learning fundamentals, and depth in at least one core domain (e.g ... Computer Vision, Sensor Fusion, Language Models, Physics-informed NNs) * Experience training models ...

Xora Innovation

VP of AI (Xora Portfolio Company)

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 Jul 11, 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.

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Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $41,731 per year, or $20.1 per hour.
Postdoctoral Research Associate in Multimodal AI and Computational Modeling for Scalable Disaster Mo

Postdoctoral Research Associate in Multimodal AI and Computational Modeling for Scalable Disaster Mo

Lehigh University

Bethlehem, PA • On-site

Full-time

Posted 24 days ago

Lehigh University rating

8.1

Company rating: 8.1 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

135th of 552 rated colleges and universities

Job description

Job Summary:
Lehigh University is seeking a motivated Postdoctoral Research Associate to contribute to research initiatives at the Center for Catastrophe Modeling and Resilience. The role involves conducting research on AI-driven disaster damage assessment and catastrophe-aware resilience modeling, while engaging in mentorship and academic service.
Responsibilities:
• Conduct independent and collaborative research in AI-driven disaster damage assessment, catastrophe modeling, multi-modal data analysis, and remote sensing analytics.
• Develop advanced Physics-informed machine learning and deep learning models for damage modeling and prediction and uncertainty quantification using multimodal geospatial datasets and numerical models.
• Design and implement scalable AI pipelines for large-scale disaster monitoring and resilience analysis.
• Prepare and publish research findings in high-impact peer-reviewed journals and present results at national and international conferences.
• Contribute to proposal writing and interdisciplinary research collaborations with academic, industry, and government partners.
• Mentor graduate and undergraduate students in research activities, data analysis, and AI model development.
• Participate in the center seminars, workshops, and collaborative research initiatives across Lehigh University.
Qualifications:
Required:
• Doctoral degree in Civil Engineering, Computer Science, Data Science, or a closely related field, completed by the start of the appointment.
• Strong background in machine learning, deep learning, computer vision, or geospatial AI.
• Experience with disaster modeling, catastrophe modeling, resilience analytics, or geospatial risk assessment.
• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Demonstrated publication record in reputable journals and conferences related to AI and Civil Engineering.
• Strong communication, collaboration, and interdisciplinary research skills.
• Ability to work independently while contributing effectively to a collaborative research environment.
Company:
Lehigh University is an American private research university located in Bethlehem, Pennsylvania. Founded in 1865, the company is headquartered in Bethlehem, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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