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Computational Physics Jobs (NOW HIRING)

Develop and productize novel computational geometry handling and meshing approaches for physics simulation (e.g., CFD, structural analysis, thermal simulation) and Physics AI workflows with a focus ...

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Computational Physicist (Early, Mid-Career, or Senior Level) I-Pulse Albuquerque LLC We are seeking ... Candidates should have a background in physics, electrical engineering, applied physics, or ...

What we Need: The SES AI Prometheus team isseeking an exceptional Computational Materials Scientist to combine physics-based simulation (DFT, MD, quantum modeling) with AI-assisted material ...

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Computational Physics information

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$142.5K

$168.8K

$192.5K

How much do computational physics jobs pay per year?

As of May 30, 2026, the average yearly pay for computational physics in the United States is $168,844.00, according to ZipRecruiter salary data. Most workers in this role earn between $155,500.00 and $182,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Computational Physicist, and why are they important?

To thrive as a Computational Physicist, you need a solid background in physics, advanced mathematics, and computer science, typically supported by a relevant degree (such as a PhD or MSc). Proficiency in programming languages like Python, C++, or Fortran, as well as experience with simulation software and high-performance computing, is essential. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate and present complex findings clearly. These skills enable accurate modeling, efficient data analysis, and successful teamwork on complex scientific projects.

What are some common challenges faced by computational physicists when working on interdisciplinary projects?

Computational physicists often collaborate with researchers from fields like engineering, chemistry, or biology, which can introduce challenges related to differing terminologies, methodologies, and priorities. Adapting complex physics models to suit the needs and constraints of other disciplines may require significant adjustments and clear communication. Additionally, integrating diverse data types and software tools can be technically demanding, but overcoming these challenges helps foster innovation and leads to broader scientific impact.

What is computational physics?

Computational physics is a branch of physics that uses computational methods and algorithms to solve complex physical problems that are difficult or impossible to address analytically. It combines physics, computer science, and applied mathematics to simulate physical systems, analyze data, and predict the behavior of matter and energy. Computational physicists often develop and use software to model phenomena such as quantum mechanics, fluid dynamics, material properties, and astrophysics. This field is essential for advancing scientific research in areas where experiments are too costly, dangerous, or impractical.

What is the difference between Computational Physics vs Data Scientist?

AspectComputational PhysicsData Scientist
Required CredentialsPhysics degree, computational skills, programmingStatistics, programming, data analysis
Work EnvironmentResearch labs, academia, scientific institutionsTech companies, finance, healthcare
Industry UsageScientific research, simulations, modelingBusiness insights, predictive analytics
Common Search/ComparisonComputational Physics vs Data Scientist

Computational Physics focuses on applying computational methods to solve physical problems, often in research or academia. Data Scientists analyze large datasets to extract insights across various industries. While both roles require programming skills, their applications and work environments differ significantly.

More about Computational Physics jobs
What cities are hiring for Computational Physics jobs? Cities with the most Computational Physics job openings:
What are the most commonly searched types of Computational Physics jobs? The most popular types of Computational Physics jobs are:
What states have the most Computational Physics jobs? States with the most job openings for Computational Physics jobs include:
Infographic showing various Computational Physics job openings in the United States as of May 2026, with employment types broken down into 79% Full Time, 19% Part Time, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $168,844 per year, or $81.2 per hour.
Computational Scientist in the Artificial Intelligence for Science (AIScience)

Computational Scientist in the Artificial Intelligence for Science (AIScience)

Princeton Plasma Physics Laboratory

Princeton, NJ โ€ข On-site

$163.60K - $261.40K/yr

Full-time

Posted 5 days ago


Job description

Overview
The Princeton Plasma Physics Laboratory (PPPL) seeks to fill a Computational Scientist in Artificial Intelligence For Science (AI4Science) position in the Computational Sciences Department. The successful candidate will establish and solicit long-term funding for a program focused on (a) foundational research in Artificial Intelligence and Machine Learning (AI/ML), and (b) application-oriented research in PPPL-relevant AI4Science topics. This is a leadership position that will strongly align with the Genesis Mission - a new initiatives in AI/ML for Science that has been launched by the Department of Energy (DOE). The incumbent will develop a fast-paced AI/ML program strategically aligned with DOE and other Federal Agency goals, ensuring that the research program advances and fits within PPPL Annual Laboratory Plans (ALP) goals.
Artificial Intelligence for Science and Energy represents a fundamental change in the scientific enterprise and an opportunity to provide foundational capabilities upon which to broaden PPPL's mission. The incumbent will build new capabilities in the Computational Sciences Department to leverage this once-in-a-generation opportunity to build an AI4Science research program at PPPL. Specifically, the incumbent will address the emerging need for AI/ML in fusion, other areas of plasma physics, and computational sciences. In addition, the incumbent will work with CSD Leadership to make key hires, build core research capabilities (including training of existing staff), and design a research program to discover new methods in data assimilation, experimental prediction, control systems, and solutions to partial differential equations.
To establish and solicit long-term funding for a program focused on (a) foundational research in Artificial Intelligence and Machine Learning (AI/ML), and (b) application-oriented research in PPPL-relevant AI4Science topics.
The Computational Sciences Department at PPPL was formed to provide a focus for computational physics and engineering. We specialize in algorithms and applied mathematics, data science and learning, high-performance computing, multiscale integrated modeling, and software technology. While our current strengths reflect the traditional focus of the Laboratory on magnetic confinement fusion (MCF), with funding from the Department of Energy's offices of Fusion Energy Sciences and the Advanced Scientific Computing Research, PPPL has always had a broad and healthy research program in areas other than MCF, including developing the theoretical and computational foundations of the dynamics and thermodynamics of naturally occurring plasmas, and more recently, in AI/ML and AI4Science.
The successful candidate will help develop the laboratory's effort in AI/ML and AI4Science, collaborating with CSD leadership and other laboratory divisions. The candidate will help establish partnerships with Princeton University and other DOE National Laboratories. The candidate will assist in recruiting new team members, seek and secure funds to support the laboratory team, and present and publish original research in this general area. The present position comes with steady-state funding for three years.
We are looking for candidates who can build a strong research program in one or more of the following topics:
  1. Machine Learning for Digital Twins, Foundation Models, and surrogates.
  2. Inference tools for interpretive analysis of experimental and simulation data.
  3. Foundational research in Machine Learning for partial differential equations (PDEs).
  4. Innovative algorithmic and methodological approaches to AI-augmented HPC application acceleration.
  5. Advanced systems and software for AI-augmented High-Performance Computing at scale.
  6. Machine-learning-driven control systems control large and complex experiments in real-time,to avoid "dangerous" conditions (disruption avoidance) using feedback systems.
  7. Scalable hybrid AI-HPC workflows using advanced capabilities.

This position requires building close collaboration with CSD Leadership, PPPL experimentists, the PPPL Theory Department, and Princeton University researchers.
A U.S. Department of Energy National Laboratory managed by Princeton University, the Princeton Plasma Physics Laboratory (PPPL) is tackling the world's toughest science and technology challenges using plasma, the fourth state of matter. With more than 70 years of history, PPPL is a leader in the science and engineering behind the development of fusion energy, a potentially limitless energy source. PPPL is also using its expertise to advance research in the areas of microelectronics, quantum sensors and devices, and sustainability sciences. Whether it be through science, engineering, technology or professional services, every team member has an opportunity to contribute to our mission and vision. Come join us!
Responsibilities
Core Duties:
  • 50% Delivering on projects (A.I. research).
  • 30% defined research.
  • 20% writing proposal building critical mass.

Qualifications
Education and Experience:
  • Ph.D. in Computer Science, Mathematics, Applied Mathematics, or a related field with core training in foundational & applied aspects of AI/ML.
  • Minimum 15 years of professional experience in an academic, scientific, or R&D environment.
  • A proven track record of publishing original results in peer-reviewed scientific journals.
  • Demonstrated scientific leadership and collaboration experience.

Working Conditions:
  • Day shift, on-site.

Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.
The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly.
If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above.
The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from participation in certain foreign government talent recruitment programs. All PPPL employees are required to disclose any participation in a foreign government talent recruitment program and may be required to withdraw from such programs to remain employed under the DOE Contract.
Standard Weekly Hours
40.00
Eligible for Overtime
No
Benefits Eligible
Yes
Probationary Period
180 days
Essential Services Personnel (see policy for detail)
No
Physical Capacity Exam Required
No
Valid Driver's License Required
No
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Salary Range
$163,600 to $261,400