Category

Engineering

Job Type

Temporary

Compensation Minimum (USD)

$25.00

Compensation Maximum (USD)

$28.00

Education

High School / GED

Minimum Citizenship Status Required

U.S Citizen or Permanent Resident

Security Clearance Required

None

Job Description

STC supports the projects and programs of the NASA Advanced Supercomputing (NAS) Division (Code TN), Computational Aerosciences Branch (Code TNA) that is part of the Exploration Technology Directorate (Code T) at the NASA Ames Research Center. The TNA team develops, enhances, and applies physics-based predictive capabilities in computational aerosciences, and performs large-scale simulations that advance the goals of the NASA Aeronautics Research and Exploration Systems Development Mission Directorates. 

Responsibilities
The position has two main categories of responsibilities:

• Familiarization with the space explorations programs supported by the Computational Aerosciences Branch and executing Computational Fluid Dynamics on the Block 2 version of the Space Launch System
• Development of new capabilities that support or add to the Computational Aerosciences

Productivity & Execution (CAPE) software. Subtasks for meaningful contributes to (2) include, but are not limited to:

• Supporting additional solvers in CAPE (Currently supported solvers are Cart3D, FUN3D, Kestrel, and OVERFLOW)
• Develop tools using neural networks or other machine learning techniques to partially automate some CAPE procedures and enable engineers to produce more results in the same amount of time.

This is a limited duration “student intern” position during the summer. The most desirable candidate will be an undergraduate student in the fields of aerospace or computer science with experience in the Python programming language and ideally experience in Computational Fluid Dynamics and machine learning.

Job Requirements

We are equal opportunity/affirmative action employers, committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, disability, or protected veteran status, or any other protected characteristic under state or local law.