Naval Systems Modeling Intern - Python/C++ & ML

Johns Hopkins Applied Physics Lab

Laurel (MD)

On-site

USD 31,000 - 66,000

Full time

14 days+

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Job summary

Johns Hopkins Applied Physics Laboratory (APL) seeks motivated interns to work on simulations of Naval capabilities, analysis tools, and early research into promising defense technologies. You will join a multi-disciplinary team in a collaborative environment focused on realistic modeling, data analysis, and robust solutions to complex problems.

Ideal candidates are pursuing engineering, CS, math, or physics degrees with strong Python or C++ skills, and a willingness to work with MBSE and signal

Qualifications

  • Pursuing a degree in Engineering, Computer Science, Math, or Physics with a minimum GPA of 3.0 (4.0 scale).
  • Detailed knowledge and practical experience in either Python or C++.
  • Interest in modeling and simulation design, signal processing related to radar or communications, decision processes, or MBSE.
  • Strong interpersonal and communication skills.
  • Eligible to obtain Interim Secret security clearance by start date and eventual Secret clearance; U.S. citizenship required.

Responsibilities

  • Develop dynamic, physics-based models/simulations to assess how physics affects sensor, C2, and weapon systems performance.
  • Develop data-analytic tools to analyze systems, diagnose issues, and propose operational solutions.
  • Advance cutting-edge concepts to improve Navy situational awareness and resource allocation in a changing battlefield.

Skills

Python
C++
Matlab

Education

Pursuing a degree in Engineering/CS/Math/Physics with GPA 3.0+

Job description

Johns Hopkins Applied Physics Laboratory (APL) seeks motivated interns to work on simulations of Naval capabilities, analysis tools, and early research into promising defense technologies. You will join a multi-disciplinary team in a collaborative environment focused on realistic modeling, data analysis, and robust solutions to complex problems.

Ideal candidates are pursuing engineering, CS, math, or physics degrees with strong Python or C++ skills, and a willingness to work with MBSE and signal

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