1

Computational Modeling Simulation Multiphysics Jobs in New Jersey

AI Overview A Calculation Engineer, also known as a Simulation Engineer, uses computational methods ... May use computer-aided design (CAD) and computer-aided engineering (CAE) software for modeling and ...

... computational technologies. Duties and Responsibilities - Develop and apply theoretical models of quantum photonic devices and systems relevant to entropy quantum computing. - Perform simulations of ...

$126K/yr

... computational technologies. Duties and Responsibilities - Develop and apply theoretical models of quantum photonic devices and systems relevant to entropy quantum computing. - Perform simulations of ...

Data Analytics & Computational Sciences Job Sub Function: Data Science Job Category: Scientific ... Hands-on experience with multi-modal ML predictive modeling and stochastic simulations for time ...

Showing results 21-40

Computational Modeling Simulation Multiphysics information

What is computational modeling simulation multiphysics?

Computational modeling simulation multiphysics refers to the use of computer-based models to simulate and analyze systems that involve multiple interacting physical phenomena—such as fluid dynamics, heat transfer, electromagnetics, and structural mechanics—all at once. This approach allows researchers and engineers to predict complex real-world behavior, optimize designs, and reduce the need for expensive prototypes. Multiphysics simulations are widely used in industries like aerospace, automotive, energy, and biomedical engineering, where accurate modeling of coupled physical processes is critical.

What are common challenges faced by professionals in computational modeling simulation multiphysics, and how can they be addressed?

One of the main challenges in Computational Modeling Simulation Multiphysics roles is managing the complexity of integrating multiple physical phenomena, such as thermal, structural, and fluid dynamics, into a single simulation. This often requires a deep understanding of both the underlying physics and the numerical methods used by simulation software. Collaborating closely with domain experts and maintaining clear communication within multidisciplinary teams can help address these challenges. Additionally, staying updated with advances in simulation tools and best practices through continuous learning is key to overcoming technical hurdles and ensuring accurate results.

What are the key skills and qualifications needed to thrive as a computational modeling simulation multiphysics engineer, and why are they important?

A strong background in physics, engineering, mathematics, and computational science—typically with an advanced degree—is essential for a Computational Modeling Simulation Multiphysics Engineer. Proficiency in simulation software such as ANSYS, COMSOL Multiphysics, MATLAB, and programming languages like Python or C++ is commonly required, along with familiarity with high-performance computing environments. Analytical thinking, problem-solving skills, and effective communication set standout professionals apart in this field. These capabilities enable accurate modeling of complex physical phenomena, efficient collaboration, and successful project outcomes in research and industry settings.

What is the difference between Computational Modeling Simulation Multiphysics vs Computational Engineer?

AspectComputational Modeling Simulation MultiphysicsComputational Engineer
CredentialsTypically requires degrees in engineering, physics, or related fields; certifications in simulation software are commonSimilar educational background; often holds engineering degrees and software certifications
Work EnvironmentPrimarily in R&D labs, engineering firms, or manufacturing settings focusing on complex simulationsInvolved in product development, software development, or systems design in various industries
Industry UsageUsed in aerospace, automotive, energy, and manufacturing for advanced simulationsApplied across industries for designing, analyzing, and optimizing systems and products

While both roles involve computational skills and engineering principles, Computational Modeling Simulation Multiphysics specializes in complex, multi-physics simulations, whereas Computational Engineer focuses on designing and implementing computational solutions across various engineering projects.

What are popular job titles related to Computational Modeling Simulation Multiphysics jobs in New Jersey?

For Computational Modeling Simulation Multiphysics jobs in New Jersey, the most frequently searched job titles are:

What job categories do people searching Computational Modeling Simulation Multiphysics jobs in New Jersey look for?

The top searched job categories for Computational Modeling Simulation Multiphysics jobs in New Jersey are:

What cities in New Jersey are hiring for Computational Modeling Simulation Multiphysics jobs?

Cities in New Jersey with the most Computational Modeling Simulation Multiphysics job openings:

Infographic showing various Computational Modeling Simulation Multiphysics job openings in New Jersey as of July 2026, with employment types broken down into 100% Full Time. Highlights an 66% In-person, and 34% Remote job distribution.

Computational Research Scientist (Two-Dimensional Materials and Low-Pressure Processing Plasma)

Princeton Plasma Physics Laboratory

Princeton, NJ • On-site

$111K - $178K/yr

Full-time

Posted 8 days ago


Job description

Overview
The Princeton Plasma Physics Laboratory (PPPL) is seeking to appoint a Computational Scientist to contribute to the advancement of modeling capabilities and physics research pertaining to using low-temperature plasmas for processing of two-dimensional materials and associated technologies. The primary responsibility of this position involves conducting and facilitating computational modeling of processing of 2D materials by low-temperature plasma for the purposes of scientific discovery and engineering design of these processes. The successful candidate will achieve this objective through the application of density functional theory (DFT) modeling of these processes using ab initio molecular dynamics (MD), and the utilization of machine learning potentials for MD acceleration.
The candidate should have strong practical familiarity with MD simulations and band gap structure calculations of 2D material properties and connection to experimental measurements. Furthermore, the candidate should demonstrate substantial practical knowledge of 2D material properties and techniques employed in plasma processing, coupled with a proven track record of modeling of such discharges. The results will be disseminated to the broader academic and industrial communities, necessitating strong interpersonal and communication skills to cultivate these relationships. Finally, this role will encompass the conceptualization and preparation of novel proposal ideas to secure funding for future research projects.
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
Application of ab initio molecular dynamics to low-temperature plasmas for processing of two-dimensional materials and associated technologies. The capabilities will be deployed for optimization of processing techniques of these materials. The candidate will be responsible for contributing to ongoing project on processing of two-dimensional materials based on transit metal dichalcogenides (50%). Defining and delivering on A.I. projects for low-temperature plasmas (20%). Proposal ideation and preparation (10%). Modeling plasma processing for industry partners (20%). Publishing scientific results and dissemination at major international conferences (10%).
Qualifications
  • Ph.D. in Physics, Engineering or a related field with core training in low-temperature plasma physics and high-performance computing.
  • Minimum 3 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 collaborative experience within academia and with industry.

Knowledge, Skills, and Abilities:
  • Extensive practical experience using first-principles methods to study materials relevant to microelectronics, quantum devices, and plasma assisted processing, including ab initio molecular dynamics and classical molecular dynamics simulations. Strong ability to connect atomistic simulation results to experimentally relevant materials properties and processing outcomes, including defect formation, surface functionalization, selective etching, plasma-induced damage, optoelectronic properties, surface cleaning, and modification of 2D materials
  • Practical knowledge of low-temperature plasma processing of materials, including plasma-assisted etching, ion/surface interactions, fluorination, oxygen and hydrogen surface chemistry, plasma activated desorption, and highly selective or self-limiting processes relevant to nanofabrication of microelectronics and quantum-device materials. Ability to develop computational workflows that support optimization of plasma processing conditions and interpretation of experimental observations
  • Advanced experience with major electronic structure, molecular dynamics, and quantum chemistry software packages, including VASP, CP2K, Gaussian, Quantum ESPRESSO, LAMMPS, and related atomistic modeling tools.
  • Strong record of scientific publication and conference presentation in electronic structure calculations, 2D materials, defects, and plasma-assisted processing of 2D materials. Ability to communicate complex computational results clearly to scientific, engineering, experimental, academic, and industrial audiences.
  • Demonstrated ability to work collaboratively in multidisciplinary research environments involving theory, computation, experiment, and industry-relevant materials processing applications. Ability to contribute to proposal ideation, preparation of research plans, development of new computational capabilities, and dissemination of results through peer-reviewed publications, talks, and major international conferences.
  • Experience in Molecular Dynamics Study of Plasma related materials like Liquid Lithium (and Boron) Interaction with H, D, and Impurities.

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
#LI-BH1
Salary Range
$111,400 to $178,000