Reduced-order Modeling - Senior Research Engineer

The Aerospace Surrogate Modeling Group at CFD Research Corporation has an opening to support modeling and simulation and development of surrogate models and reduced-order models for aerospace vehicles. The engineer will join CFD Research's Aerospace Machine Learning Group and support R&D programs through development and demonstration of surrogate modeling and reduced-order modeling techniques for providing rapid approximations of aerospace systems. The engineer will be responsible for:

• Developing surrogate modeling techniques for efficient approximations of aerospace vehicles
• Demonstrating, validating, and verifying surrogate model accuracy
• Support integration of government and commercial off-the-shelf tools with in-house surrogate modeling and reduced-order modeling tools

Requirements:

• 3+ years of experience in reduced-order modeling or surrogate modeling
• Proficiency with the Python programming languag
• Working knowledge of software development practices, including git software configuration management
• Excellent proactive communication (oral, written, presentation), interpersonal, and organizational skills
• Ability to successfully complete assigned tasks with general supervision and oversight
• Candidate must be a US Citizen and meet eligibility to obtain/maintain a Security Clearance

Preferred Qualities:

• Experience with computational fluid dynamics, structural dynamics, or electromagnetics
• Experience with surrogate modeling for design of experiments or optimization
• Experience with PyTorch, pyDACE, or surrogate modeling toolbox
• Experience with C++, Java, C#
• Ambitious, hardworking, and driven towards continuous growth
• Strong analytical problem-solving skills with the ability to devise creative software design solutions
• Proven ability to engage multiple stakeholders and provide recommendations to technical decisions
  
  

Location: This role is based at CFD Research Corporate headquarters, in the Huntsville, AL area, and is 100% onsite. There may opportunity for Telework flexibility, depending on experience level.

About the Group: CFD Research's Aerospace Machine Learning Group is developing a portfolio of traditional modeling and simulation, machine learning, and reduced-order modeling tools for supporting aerospace R&D. This includes development of predictive machine learning and reduced-order models for (1) rapid estimation of aerospace vehicle properties; (2) optimal data collection through intelligent adaptive design of experiment techniques; (3) affordable uncertainty quantification; and (4) multi-disciplinary design optimization.

About CFD Research: Since its inception in 1987, CFD Research has been a technology leader in engineering simulations and innovative designs. CFD Research has worked with government agencies, businesses, and academia to provide innovative solutions within the Aerospace & Defense, Biomedical & Life Sciences, and Energy & Materials industries. CFD Research has earned multiple national awards for successful application and commercialization of innovative technology prototypes, multi-physics simulation software, multi-disciplinary analyses, and expert support services. CFD Research's impressive three-year growth rate was high enough to recognize the company in the Inc. Magazine's 5000 for the second year in a row.

Benefits: CFD Research offers competitive salaries and excellent employee benefits, including an employer matching 401(k) and Employee Stock Ownership Plan (ESOP). CFD Research offers a highly competitive insurance package, including medical, vision, and dental insurance. We offer company paid leave, compensation time, parental leave, long-term disability, accidental death and dismemberment, and life insurance. Performance appraisals occur twice a year and annual pay increases are based upon corporate goals, personal development, performance, and outstanding achievements. In addition, group and individual bonuses are awarded for exceptional performance.

CFD Research is an EO employer - Veterans/Disabled and other protected categories