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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
Senior Modeling & Simulation Engineer

Senior Modeling & Simulation Engineer

Scientific Research Corporation

Alexandria, VA • On-site

$111K - $153K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago

Job description

Description
Seeking a highly skilled and innovative Senior Modeling & Simulation (M&S) Engineer to provide critical technical oversight for the Department of War (DoW) in the development of next-generation hypersonic systems.
The DoW Test Resource Management Center (TRMC) is at the forefront of fielding advanced capabilities to ensure a decisive edge for the warfighter. This position provides an opportunity to join a premier Systems Engineering and Technical Advisor (SETA) contractor team, guiding government investment in the digital infrastructure that underpins the entire hypersonic test and evaluation enterprise. The ideal candidate is a subject matter expert in multi-physics M&S who is passionate about integrating high-fidelity models with physical test campaigns and leveraging digital engineering to accelerate development.
Key Responsibilities:
Under the oversight of the Chief Engineer, the candidate will:
Serving as the lead technical expert on behalf of the government program office to oversee a portfolio of advanced M&S projects
  • Working within a highly collaborative, integrated team of engineers and project managers to ensure the government's technical and programmatic objectives are achieved
  • Providing direct government oversight for the development and integration of the Digital Engineering (DE) elements for high priority hypersonic test and evaluation infrastructure modernization projects
  • Championing the integration of Artificial Intelligence (AI) and Machine Learning (ML) into physics-based models to enhance predictive capabilities and accelerate analysis
  • Assessing contract performer strategies for creating and maintaining the "Digital Thread," ensuring data continuity from requirements definition in Model-Based Systems Engineering (MBSE) models through design, simulation, test, and operations
  • Providing technical oversight for the development of cloud-based digital engineering environments, ensuring the seamless integration of M&S tools, data repositories, and program management software
  • Conducting detailed technical reviews of contractor-developed M&S tools, methodologies, and validation plans, ensuring they meet government requirements for fidelity and accuracy
  • Assessing contractor performer approaches to multi-physics coupling (e.g., aerodynamics, aerothermodynamics, structural response) and the integration of M&S with physical test data
  • Evaluating and providing technical feedback on the performer's Verification, Validation, and Accreditation (VV&A) plans and results for all models and simulations
  • Serving as a key technical advisor during all performer-driven project reviews, including the System Requirements Review (SRR), Integrated Baseline Review (IBR), Preliminary Design Review (PDR), Critical Design Review (CDR), and Technical Interchange Meetings (TIMs), with a focus on M&S-related content
  • Preparing and presenting clear, concise technical assessments, white papers, and recommendations to the Chief Engineer and Government Program Manager regarding M&S development, risks, and opportunities
  • Reviewing and providing technical input on contract deliverables such as the Systems Engineering Plan (SEP), Integrated Master Schedule (IMS), and other program documentation related to M&S
  • Leading the SETA team's efforts to adopt and utilize GenAI and other advanced digital tools to improve the efficiency and effectiveness of technical oversight
  • Communicating complex M&S and digital engineering concepts and findings effectively to both technical and non-technical stakeholders

#LI-HK1
Requirements
  • Bachelor's degree in aerospace engineering, Mechanical Engineering, Physics, or a related field and 10+ years of relevant experience
  • Demonstrated expertise in Digital Engineering principles, methodologies, and their application, including direct experience with Model-Based Systems Engineering (MBSE), Digital Thread, and Digital Twin concepts
  • Strong understanding of the components of a digital ecosystem, such as Product Lifecycle Management (PLM) tools, data management and protection, and high-performance computing (HPC) environments and their application to engineering workflows
  • Demonstrated hands-on experience developing or applying advanced computational models (e.g., CFD, FEA, trajectory simulation) to complex aerospace systems
  • Proven expertise in at least one of the following M&S domains: aerodynamics, aerothermodynamics, combustion, or structural mechanics
  • Strong understanding of cloud computing environments (e.g., AWS GovCloud, Azure Government) and their application to engineering workflows
  • Excellent written and verbal communication skills, with demonstrated experience writing detailed technical reports and presenting engineering briefings to communicate status, findings, and risks.
  • Experience working collaboratively in a cross-functional or matrixed engineering team environment
  • Organized, detail-oriented, and able to work independently with minimal supervision
  • Proficiency using Microsoft Office Software including Outlook, Word, PowerPoint, and Excel
  • Currently hold a Secret security clearance

Desired Skills
  • Master's Degree or Ph.D. in a relevant engineering or science discipline
  • Specific experience with M&S of hypersonic, high-temperature, or reacting flow fields
  • Demonstrated understanding of Artificial Intelligence (AI) / Machine Learning (ML) techniques and their application to engineering analysis or data-driven modeling
  • Experience evaluating the technical performance of other Government contractors
  • Familiarity with DoW weapon acquisition programs and the role of T&E in system development
  • Knowledge of large-scale data management strategies and standardized data formats (e.g., HDF5)
  • Hands-on experience with MBSE tools such as Cameo Systems Modeler and proficiency with the Systems Modeling Language (SysML)
  • Familiarity with Product Lifecycle Management (PLM) software (e.g., Windchill) and modern DevSecOps/collaboration tools (e.g., Jira, Confluence, GitLab)
  • Eligibility for a Top Secret security clearance

Clearance Information
SRC IS A CONTRACTOR FOR THE U.S. GOVERNMENT, THIS POSITION WILL REQUIRE U.S. CITIZENSHIP AS WELL AS, A U.S. GOVERNMENT SECURITY CLEARANCE AT THE SECRET LEVEL
Travel Requirements
  • Travel approximately 20% of the year (~10 non-consecutive weeks) to performer worksites and government offices to observe development activities and participate in reviews and meetings

About Us
Scientific Research Corporation is an advanced information technology and engineering company that provides innovative products and services to government and private industry, as well as independent institutions. At the core of our capabilities is a seasoned team of highly skilled engineers and scientists with multidisciplinary backgrounds. This team is challenged daily to provide cutting edge technology solutions to our clients.
SRC offers a generous benefit package, including medical, dental, and vision plans, 401(k) with a company match, life insurance, vacation and sick paid time off accruals starting at 10 days of vacation and 5 days of sick leave annually, 11 paid holidays, tuition reimbursement, and a work environment that encourages excellence and more. For positions requiring a security clearance, selected applicants will be subject to a government security investigation and must meet eligibility requirements for access to classified information.
EEO
Scientific Research Corporation is an equal opportunity employer that does not discriminate in employment. All qualified applicants will receive consideration for employment without regard to their race, color, religion, sex, age, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other protected characteristic under federal, state or local law.
Scientific Research Corporation endeavors to make www.scires.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact jobs@scires.com for assistance. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications.

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