Associate Computational Scientist in the Artificial Intelligence for Science (AIScience)

Requisition # 2025-21008
Date Posted 23 hours ago(7/31/2025 11:00 AM)
Department
PPPL Computational Science
Category
Research and Laboratory
Job Type
Full-Time

Overview

The Princeton Plasma Physics Laboratory (PPPL) seeks to fill an Associate Computational Scientist (“post-doc”) in Artificial Intelligence for Science (AI4Science) position in the Computational Sciences Department. The successful postdoc candidate will help build a research 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 position will help grow new initiatives in AI/ML that are being planned by the Department of Energy (DOE). The incumbent will work in 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 help grow the computer science and distributed infrastructure aspects underpinning AI4Science at scale. In addition, the incumbent will be mentored and work with CSD Leadership, participate in building core research capabilities, and support the growth and design of a research program to discover new methods in data assimilation, experimental prediction, control systems, and solutions to partial differential equations.

 

To advance PPPL’s mission in artificial intelligence for science by supporting strategic projects, conducting original AI/ML research, to grow a nationally aligned, application-driven research portfolio in AI4Science.

 

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 support the laboratory’s effort in AI/ML and AI4Science, collaborating with CSD leadership and other laboratory divisions. The candidate will 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 are looking to join a growing and evolving AI/ML research area. Areas of research that PPPL supports are the following topics:

  1. Machine Learning for Digital Twins, Foundation Models, and surrogates (surrogate model building from our suite of fusion codes, new optimization techniques, and differentiable programming).
  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.

This position requires 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: 

  • Direct Research - 80%.
  • Dissemination and Publications - 20%. 

Qualifications

Education and Experience: 

  • Must have a Ph.D. in Computer Science, Mathematics, Applied Mathematics, or a related field with core training in foundational & applied aspects of AI/ML.
  • 0-2 years after PhD.
  • A proven track record of publishing original results in peer-reviewed scientific journals.
  • Demonstrated scientific collaboration experience.

Knowledge, Skills and Abilities: 

  • Strong written and verbal communication. Must command a strong understanding of English grammar and syntax.
  • Ability to work in a dynamic and a fast-moving team; must be able to demonstrate this.
  • This postdoc position will be generating and testing with experimental code and prototypes, not established software. Must be willing to be open to learning new codes and prototypes.

Working Conditions: 

  • This position will be in a dry Lab/semi industrial site. Day shift on-site. 

 

Princeton University is an Equal Opportunity 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

$91,500 to $146,100

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If you are a qualified individual with a disability and are, therefore, unable or limited in your ability to use or access this system, you can request a reasonable accommodation by contacting PPPL's Office of Human Resources at Onboarding@pppl.gov.

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.

Princeton University-PPPL job offers are contingent upon the candidate’s successful completion of a background check, reference checks, and pre-employment screening, as applicable.

PPPL is a U.S. Department of Energy (DOE) national laboratory managed by Princeton University. The 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.

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