Missile Defense Engineer/Scientist Intern

Johns Hopkins Applied Physics Laboratory; Laurel (MD); On-site; USD 31,000 - 66,000; Full time

Job summary

Johns Hopkins Applied Physics Laboratory (APL) is offering exciting summer internship opportunities within the Cross‑Domain Battle Management Group. Interns will work on defense and space domain challenges, bridging missile defense and complex systems engineering to support national security interests.

Qualified students pursuing STEM degrees with a 3.0+ GPA can gain hands‑on experience in R&D, data analysis, algorithm evaluation, and AI/ML techniques while collaborating across teams in a

Qualifications

• Pursuing a Bachelor’s, Master’s, or Doctoral degree in Electrical Engineering, Computer Science, Physics, Mathematics, Data Science, Statistics, or similar with a 3.0 GPA+.
• Working knowledge of MATLAB, Python, Java, C, and/or C++.
• Desire to apply engineering skills to complex problems and strong communication skills.
• Eligible to obtain Interim Secret clearance by start date and eventual Secret clearance. U.S. citizenship required.

Responsibilities

• Assist staff in R&D activities identifying gaps in U.S. Missile Defense systems.
• Analyze data from sensor and missile test events.
• Evaluate algorithms developed by group staff and test solutions.
• Contribute to AI/ML approaches for solving complex national security problems.
• Collaborate in a team-oriented environment to develop and test technical solutions.

Skills

Written communication

Problem solving

Teamwork

Education

Bachelor's/Master's/PhD in EE/CS/Physics/Math/Data Science/Statistics

GPA 3.0+

Tools

MATLAB

Python

Java

C

C++

Job description

Johns Hopkins Applied Physics Laboratory (APL) is offering exciting summer internship opportunities within the Cross‑Domain Battle Management Group. Interns will work on defense and space domain challenges, bridging missile defense and complex systems engineering to support national security interests.

Qualified students pursuing STEM degrees with a 3.0+ GPA can gain hands‑on experience in R&D, data analysis, algorithm evaluation, and AI/ML techniques while collaborating across teams in a