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The Structural & Thermal-Fluids Engineering Group provides innovative multidisciplinary engineering solutions for underwater, ground, air, and space-based prototype systems for national security applications. Examples include aerodynamic designs and multifunctional materials for airborne sensors, hypersonic platforms, and unmanned aerial vehicles, and the development of structural-material systems for space-based imaging and laser communication terminals, thermal management for high energy laser systems and RF solid-state devices. Engineering solutions are developed through the utilization of appropriate technologies coupled with high-fidelity models and multidisciplinary simulations, environmental and performance characterization testing, and the utilization and development of advanced materials to optimize solutions to meet ever increasing performance, size, weight, and environmental challenges.

Position Description

Overview

Group 7-74 is seeking a highly motivated Spring 2026 Co-op student (approximately January through June) with an interest in applying novel machine learning techniques to solve aerospace engineering problems, for example, predicting the fluid dynamics around a vehicle. Duties could include the following: researching and implementing novel deep learning techniques, creating and running analysis models (CFD models, flight dynamics models, etc.), running of internally-developed multidisciplinary simulation software, analysis, research and development of new capabilities, and engineering design. The group values well-rounded candidates with a foundation in software development, and places strong emphasis on teamwork, adaptability, diversity of thought, and technical skills.

Required Qualifications

+ Currently enrolled in an undergraduate or graduate engineering program(Preferred majors: Computer Science, Aerospace Engineering, Mechanical Engineering)

+ Completion of a Machine Learning course

+ Knowledge of fluid mechanics and aerodynamics

+ Programming experience in Python, Julia, or similar languages

+ GPA of 3.0 or higher on a 4.0 scale

Preferred Qualifications

+ Completion of coursework in fluid mechanics and/or aerodynamics

+ Experience with physics-informed machine learning techniques for solving PDEs

Compensation for 2025 (will be reviewed for 2026)

+ Technical Co-Op: $24.50 – $31.00 per hour (based on year in school)

+ Administrative Co-Op: $21.50 – $25.00 per hour (based on year in school)

Selected candidate will be subject to a pre-employment background investigation and must be able to obtain and maintain a Secret level DoD security clearance.

MIT Lincoln Laboratory is an Equal Employment Opportunity (EEO) employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, or genetic information; U.S. citizenship is required.

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