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Computational Modeling Simulation Multiphysics Jobs in Virginia

Demonstrated experience with agent-based modeling, micro-simulation, computational social science, or modeling socio-technical systems. * Experience using game engines such as Unity and Unreal.

Demonstrated experience with agent-based modeling, micro-simulation, computational social science, or modeling socio-technical systems. * Experience using game engines such as Unity and Unreal.

Demonstrated experience with agent-based modeling, micro-simulation, computational social science, or modeling socio-technical systems. * Experience using game engines such as Unity and Unreal.

SIERRA Modeling and Simulation (M&S) Subject Matter Expert (SME) Location: Reston, VA Clearance ... The ideal candidate will have a strong academic background in computational fluid dynamics (CFD ...

Working along experts in AI, Machine Learning, computational modeling, and distributed systems, you ... You have 3+ years professional experience (or an advanced degree) in model and simulation ...

Working along experts in AI, Machine Learning, computational modeling, and distributed systems, you ... You have 3+ years professional experience (or an advanced degree) in model and simulation ...

Working along experts in AI, Machine Learning, computational modeling, and distributed systems, you ... You have 3+ years professional experience (or an advanced degree) in model and simulation ...

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Computational Modeling Simulation Multiphysics information

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 are some common challenges faced by professionals in Computational Modeling Simulation Multiphysics roles, 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 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 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 Virginia? For Computational Modeling Simulation Multiphysics jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Computational Modeling Simulation Multiphysics jobs in Virginia look for? The top searched job categories for Computational Modeling Simulation Multiphysics jobs in Virginia are:
What cities in Virginia are hiring for Computational Modeling Simulation Multiphysics jobs? Cities in Virginia with the most Computational Modeling Simulation Multiphysics job openings:
Term Assistant Professor, Computational and Data Sciences

Term Assistant Professor, Computational and Data Sciences

George Mason University

Fairfax, VA • On-site

Full-time

Posted 19 days ago


George Mason University rating

8.3

Company rating: 8.3 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

92nd of 529 rated colleges and universities


Job description

Department: College of Science
Classification: 9-month Instructional Faculty
Job Category: Instructional Faculty
Job Type: Full-Time
Work Schedule: Full-time (1.0 FTE, 40 hrs/wk)
Location: Fairfax, VA
Workplace Type: Hybrid Eligible
Sponsorship Eligibility: Not eligible for visa sponsorship
Salary: Salary commensurate with education and experience
Criminal Background Check: Yes
Works with Minors check: Yes
About the Department:
The Department of Computational and Data Sciences (CDS) (https://sciences.gmu.edu/cds) at George Mason University (GMU) is a rapidly growing department for data science and computing innovation. Part of the College of Science, CDS advances state-of-the-art research and delivers top-tier education at both undergraduate and graduate levels.
The Department offers a Bachelor of Science in Computational and Data Science. This program integrates data analytics, modeling, and scientific computing to prepare students for careers in industry, government, and beyond. CDS provides career advancement opportunities for graduate students through its M.S. in Computational Science, Ph.D. in Computational Sciences and Informatics, and Ph.D. in Computational Social Science. These programs emphasize technical expertise and the interdisciplinary applications of computation, modeling & simulation, and data-driven discovery.
Complementing its educational mission, CDS faculty develop, conduct, and disseminate cutting-edge, externally funded interdisciplinary research in diverse application areas where computational science, data science, and modeling & simulation are essential. Its recent research portfolio includes funding from the National Science Foundation (NSF), Defense Threat Reduction Agency (DTRA), Central Intelligence Agency (CIA), Intelligence Advanced Research Projects Activity (IARPA), Department of Homeland Security (DHS), and the U.S. Department of the Army.
Through collaborations with government and industry partners at both regional and national levels, the department strives to ensure its research remains competitive. In alignment with the broader mission of GMU and the College of Science, CDS is also strongly committed to engagement, working with high school, undergraduate, and graduate students, as well as stakeholder communities through research opportunities, internships, summer programs, and collaborations within and beyond the university.
George Mason University College of Science (Mason Science) is committed to advancing inclusive excellence and fostering an environment free from discrimination, harassment, and retaliation throughout our STEM community. At Mason Science, our values include cultivating an organizational culture that promotes belonging, respect, and civility. We believe that varied opinions, cultures, and perspectives are what provides vibrancy, innovation, and growth to an academic community. By prioritizing cultural responsiveness in academics, teaching, research, and global engagement, we strive to attract faculty and staff who exemplify the Mason Science mission and vision.
About the Position:
The position in the Department of Computational and Data Sciences (CDS) will support the department's efforts to achieve its mission in education and engagement. The successful Term Assistant Professor is expected to: (a) teach at both the undergraduate and graduate levels, develop new course curriculum, and support the department's undergraduate, certificate, Master, and two PhD programs; and (b) participate and contribute to service at the department, college, university, and relevant scientific communities/organizations, as well as support department activities to promote its programs.
Responsibilities:
  • Teach courses offered by CDS at the undergraduate and graduate levels in all course modalities (in-person, hybrid, and fully online) as assigned, develops new courses in area(s) of expertise, and supports teaching activities across undergraduate, certificate, and graduate programs in the department; holds office hours, mentors students, and supervises graduate and undergraduate student research, which may also include the oversight of GTAs, GRAs and department Student Teachers and Research (STAR) Assistants.
  • Service to the department, college, and university: serves on department standing and ad-hoc committees, supports department efforts to grow and promote the department and its programs, and serves on college- and university-level committees appropriate for career stage and experience.

Required Qualifications:
  • Doctoral degree in a closely related field including Data Science, Information Science, Scientific Computing, Computational Science, Artificial Intelligence, Simulation, or Modeling is required prior to starting this appointment;
  • One year of experience teaching at the undergraduate level as a teaching assistant or instructor of record;
  • Demonstrated commitment to ethics and professional values;
  • Knowledge and skills in developing, delivering, and maintaining high quality curriculum and instruction at the undergraduate level in the following areas: data science foundations, data science ethics, scientific computing, and artificial intelligence;
  • Ability to mentor undergraduate and graduate students and guide students in their academic and professional growth;
  • Knowledge for and ability to develop new courses in one of more fields of specialization;
  • Ability to communicate with students, faculty, and staff effectively; and
  • Strong interpersonal skills to build professional relationships with students, faculty, and staff.

Preferred Qualifications:
  • Demonstrated record of excellence in teaching at the undergraduate level;
  • Two or more years of experience teaching at the undergraduate level as a teaching assistant or instructor of record;
  • Two or more years of experience working in a computational and data sciences field in an industry or government setting;
  • Experience teaching multi-section courses and large courses;
  • Demonstrated teaching record that combines Artificial Intelligence and/or Machine Learning with one or more of the following areas: Scientific Computing, Modeling, Simulation, Scientific Visualization, or Computational Social Science;
  • Experience developing and maintaining course curriculum and materials;
  • Experience developing and/or implementing innovative teaching and student engagement methods;
  • Experience with a variety of technical environments commonly used in computational science and data science, including relevant software and hardware;
  • Strong knowledge and familiarity with the foundation and state-of-the-art in modeling and simulation, databases, data visualization, and high-performance computing;
  • Knowledge in other areas that align with or strongly complement those of the department curriculum;
  • Knowledge of best practices for developing and delivering course curriculum;
  • Outstanding verbal and written communication skills;
  • Excellent organizational and time management skills;
  • Ability to work and collaborate effectively in group settings;
  • Ability to work and collaborate effectively in interdisciplinary groups; and
  • Commitment to mentoring and educating a broad range of students, particularly those who are traditionally underrepresented in STEM.

Instructions to Applicants:
For full consideration, applicants must apply for the Term Assistant Professor, Computational and Data Sciences at https://jobs.gmu.edu/. Complete and submit the online application to include three professional references with contact information, and provide a letter of intent, CV, philosophy of teaching, and an unofficial copy of transcript (required only for candidates with less than 2 years of post-PhD experience).
Posting Open Date: February 9, 2026
For Full Consideration, Apply by: March 9, 2026
Open Until Filled: Yes
Mason Ad Statement
Mason is currently the largest and most diverse university in Virginia with students and faculty from all 50 states and over 135 countries studying in over 200 degree programs at campuses in Arlington, Fairfax and Prince William, as well as at learning locations across the commonwealth. Rooted in Mason's diversity is a campus culture that is both rewarding and exciting, work that is meaningful, and opportunities to both collaborate and create.
If you are interested in joining the Mason family take a look at our current opportunities and catch some Mason spirit at jobs.gmu.edu/!
George Mason University, Where Innovation is Tradition.
Equity Statement
George Mason University is an equal opportunity/affirmative action employer, committed to promoting inclusion and equity in its community. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any characteristic protected by law.
Campus Safety Information
Mason's Annual Security and Fire Safety Report is available at http://police.gmu.edu/annual-security-report/

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