Fielded Engine Performance Intern: Data & Modeling

GE Aerospace; Santiago de Querétaro; On-site; MXN 89,000 - 134,000; Full time

Job summary

GE Aerospace in Querétaro seeks a Fielded Engine Performance intern to support the development and sustainment of physics-based models for fielded commercial engines across GE Engine lines. You will analyze large data sets and update models for Prognostics and Health Management, Engine Control Systems, and Engine Performance teams.

Collaborate with global teams, present findings, and learn through hands-on projects, data quality assessment, and root-cause analysis to drive improvements in engine

Qualifications

• Engineering bachelor candidate in CS, electronics, mechanical, aeronautical, mechatronics or equivalent, within one year of graduation.
• Proficiency in object-oriented programming or experience with C, C++, R, Python, or similar.
• Experience with thermodynamics and fluid dynamics.
• Effective written and oral English communication skills.
• Availability of 40 hours per week; in-person work at GEIQ facilities.

Responsibilities

• Data quality assessment and statistical analysis.
• Broadening knowledge of own technical discipline to execute policy/strategy.
• Participate in root cause analysis on field events.
• Present and substantiate results to senior leadership and direct manager.
• Show proactivity and autonomy in learning new processes and programming technique.

Skills

Object-oriented programming

C/C++/Python experience

Thermodynamics & fluid dynamics

English communication skills

Availability 40 hours per week

Education

Engineering bachelor in CS/Electrical/Mechanical/Aeronautical/Mechatronics or equivalent, within one year of graduation

Job description

GE Aerospace in Querétaro seeks a Fielded Engine Performance intern to support the development and sustainment of physics-based models for fielded commercial engines across GE Engine lines. You will analyze large data sets and update models for Prognostics and Health Management, Engine Control Systems, and Engine Performance teams.

Collaborate with global teams, present findings, and learn through hands-on projects, data quality assessment, and root-cause analysis to drive improvements in engine