Propulsion Analysis Intern: Cycle Modeling & Performance

Gulfstream Aerospace; Savannah (GA); On-site; USD 28,000 - 34,000; Full time

Benefits offered by this job

Housing

Competitive pay

Medical coverage

Paid Time Off

401(k) match

Mentorship

Collegiate networking events

Job summary

Gulfstream Aerospace in Savannah, GA is seeking a Spring 2027 Flight Sciences Propulsion College Intern to apply classroom learning to real-world propulsion challenges. You will work with the Propulsion Analysis team on engine cycle analysis, modeling, and certification-related activities, mentored by experienced engineers.

The role offers hands-on experience in engine cycle analysis, propulsion system modeling, and performance evaluation across programs and future tech efforts.

Qualifications

• Must be enrolled in an accredited university pursuing a bachelor's degree or higher.
• Cumulative GPA of 3.0 (without rounding); must be listed on resume.
• Must be available to work on-site in Savannah, GA during the Spring 2027 semester.

Responsibilities

• Support development and maintenance of engine cycle simulation models.
• Perform off-design engine performance analyses and trade studies.
• Analyze engine and aircraft performance data.
• Support studies related to fuel consumption, thrust performance, operability, and mission analysis.
• Assist with validation of analytical models using available test or flight data.
• Document methods, assumptions, and analysis results for engineering use.

Skills

NPSS

AxSTREAM

Education

Enrolled in bachelor's degree or higher

Tools

MATLAB/Simulink

Excel/VBA

Python

Job description

Gulfstream Aerospace in Savannah, GA is seeking a Spring 2027 Flight Sciences Propulsion College Intern to apply classroom learning to real-world propulsion challenges. You will work with the Propulsion Analysis team on engine cycle analysis, modeling, and certification-related activities, mentored by experienced engineers.

The role offers hands-on experience in engine cycle analysis, propulsion system modeling, and performance evaluation across programs and future tech efforts.