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Machine Learning Cfd Jobs in Virginia (NOW HIRING)

QinetiQ

Mechanical Engineer

Lorton, VA

... machine learning (ML), and augmented reality (AR). QinetiQ US's dedicated experts in defense ... Computational Fluid Dynamics (CFD) * Experience in additive manufacturing design, methods, and ...

QinetiQ US

Mechanical Engineer

Lorton, VA · On-site

... machine learning (ML), and augmented reality (AR). QinetiQ US's dedicated experts in defense ... Computational Fluid Dynamics (CFD) * Experience in additive manufacturing design, methods, and ...

QinetiQ US

Mechanical Engineer

Lorton, VA

... machine learning (ML), and augmented reality (AR). QinetiQ US's dedicated experts in defense ... Computational Fluid Dynamics (CFD) * Experience in additive manufacturing design, methods, and ...

QinetiQ US

Mechanical Engineer

Lorton, VA

... machine learning (ML), and augmented reality (AR). QinetiQ US's dedicated experts in defense ... Computational Fluid Dynamics (CFD) * Experience in additive manufacturing design, methods, and ...

QinetiQ

Mechanical Engineer

Lorton, VA · On-site

... machine learning (ML), and augmented reality (AR). QinetiQ US's dedicated experts in defense ... Computational Fluid Dynamics (CFD) * Experience in additive manufacturing design, methods, and ...

QinetiQ US

Mechanical Engineer

Lorton, VA · On-site

... machine learning (ML), and augmented reality (AR). QinetiQ US's dedicated experts in defense ... Computational Fluid Dynamics (CFD) * Experience in additive manufacturing design, methods, and ...

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All JobsMachine Learning Cfd JobsMachine Learning Cfd Jobs in Virginia

Machine Learning Cfd information

What are Machine Learning CFD jobs?

Machine Learning CFD (Computational Fluid Dynamics) jobs focus on integrating machine learning techniques with traditional fluid dynamics simulations and analyses. Professionals in this field use AI and data-driven models to accelerate simulations, improve prediction accuracy, and optimize fluid flow processes. These roles often require knowledge of both CFD principles and machine learning algorithms, and are commonly found in industries such as aerospace, automotive, and energy. Typical responsibilities include developing surrogate models for simulations, automating data analysis, and implementing deep learning approaches for complex flow problems.

How does a Machine Learning CFD professional typically collaborate with domain experts and software engineers in a project setting?

As a Machine Learning CFD (Computational Fluid Dynamics) professional, you’ll frequently collaborate with domain experts such as mechanical or aerospace engineers to ensure your models accurately reflect physical phenomena. You’ll also work closely with software engineers to integrate machine learning algorithms into simulation pipelines and optimize computational performance. Effective communication is key, as you’ll need to translate complex data-driven insights into actionable engineering solutions and vice versa. These collaborative efforts help streamline workflows, improve model accuracy, and ensure practical deployment of ML-enhanced CFD tools.

What is the difference between Machine Learning CFD vs Data Scientist?

AspectMachine Learning CFDData Scientist
Required CredentialsDegree in Engineering, Computer Science, or related fields; knowledge of CFD softwareDegree in Statistics, Computer Science, or related fields; strong programming skills
Work EnvironmentEngineering firms, aerospace, automotive industries, research labsBusiness, finance, tech companies, research institutions
Industry UsageSimulation, fluid dynamics, engineering analysisData analysis, predictive modeling, business insights

Machine Learning CFD focuses on applying machine learning techniques to computational fluid dynamics simulations, often within engineering contexts. Data Scientists analyze large datasets to extract insights and build predictive models across various industries. While both roles require programming skills and a strong analytical background, Machine Learning CFD emphasizes simulation and engineering applications, whereas Data Scientists focus on data-driven decision-making across diverse sectors.

What are the key skills and qualifications needed to thrive as a Machine Learning CFD (Computational Fluid Dynamics) Engineer, and why are they important?

To thrive as a Machine Learning CFD Engineer, you need a strong background in fluid dynamics, numerical methods, and machine learning, often supported by a degree in engineering, physics, or computer science. Familiarity with CFD software (such as ANSYS Fluent or OpenFOAM), programming languages like Python or C++, and machine learning frameworks (TensorFlow or PyTorch) is essential. Critical thinking, problem-solving, and effective communication are standout soft skills for interpreting data and collaborating on interdisciplinary teams. These competencies are crucial for developing innovative solutions that enhance simulation accuracy and computational efficiency in engineering projects.
What are popular job titles related to Machine Learning Cfd jobs in Virginia? For Machine Learning Cfd jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Machine Learning Cfd jobs in Virginia look for? The top searched job categories for Machine Learning Cfd jobs in Virginia are:
What cities in Virginia are hiring for Machine Learning Cfd jobs? Cities in Virginia with the most Machine Learning Cfd job openings:
Machine Learning Cfd jobs near you
Research Associate in Mechanical and Aerospace Engineering

Research Associate in Mechanical and Aerospace Engineering

University of Virginia

Charlottesville, VA • On-site

$53K/yr

Full-time

Posted 5 hours ago

University Of Virginia rating

7.8

Company rating: 7.8 out of 10

Based on 34 frontline employees who took The Breakroom Quiz

198th of 541 rated colleges and universities

Job description

The Computational Fluid Dynamics (CFD) and Propulsion Laboratory in the Department of Mechanical and Aerospace Engineering at University of Virginia is seeking a qualified candidate for a Postdoctoral Research Associate position.
Research in the laboratory focuses on high-performance computing (HPC) methods in CFD, advanced algorithm development, data assimilation and scientific machine learning. The successful candidate will contribute to the development of advanced numerical algorithms for large-scale CFD modeling and simulations, including scalable solvers, domain decomposition methods, and data-driven and physics-driven learning techniques.
The Postdoctoral Research Associate will work as an algorithm developer within the CFD and Propulsion Laboratory and will be responsible for the development, implementation, and analysis of efficient numerical methods for next-generation CFD applications on HPC platforms.
Qualification Requirements
By the start date, applicants must have earned a PhD in Mathematics or Statistics or other related field, and be within 5 years post-PhD. Candidates should demonstrate research experience in a few of the following areas:
  • CFD methods, numerical methods and analysis, stability analysis
  • Scalable solvers, and domain decomposition methods
  • C++ programming, parallel programming
  • Stochastic partial differential equations (PDEs), stochastic processes and analysis
  • Model reduction, surrogate model development
  • Uncertainty quantification

Preferred Qualifications
Preference will be given to candidates with additional expertise in:
  • AI/ML
  • Supercomputing
  • Peer-reviewed publications in computational mathematics and/or computational/numerical methods

Salary
The anticipated hiring base salary is $53,000.
Application Procedure
Apply online through the UVA Job Board and search for position number R0083690.
Applicants should upload:
  • A cover letter
  • Curriculum vitae
  • Contact information for three professional references

Please note that multiple documents may be uploaded in the application portal.
Application Deadline
Review of applications will begin on June 2, 2026; however, the position will remain open until filled. The University will perform background checks on all new hires prior to employment.
This is a one-year appointment. Renewal is contingent upon available funding and satisfactory performance.
Questions regarding this position should be directed to Professor Xinfeng Gao at gao@virginia.edu .
For questions about the application process, please contact Richard Haverstrom, Academic Recruiter, at rkh6j@virginia.edu .
For more information on the benefits available to Research Associate at UVA, visit hr.virginia.edu/benefits.
The University of Virginia is an equal opportunity employer. All interested persons are encouraged to apply, including veterans and individuals with disabilities. Learn more about UVA's commitment to non-discrimination and equal opportunity employment .

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About University of Virginia

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The University of Virginia is distinctive among institutions of higher education. Founded by Thomas Jefferson in 1819, the University sustains the ideal of developing, through education, leaders who are well-prepared to shape the future of the nation.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Charlottesville, VA, US

Year founded

1819

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