Autonomous Systems Design Engineer (PhD Track)

The Johns Hopkins University Applied Physics Laboratory; Laurel (MD); On-site; USD 105,000 - 245,000; Part time

Job summary

The Johns Hopkins University Applied Physics Laboratory (APL) is seeking PhD candidates in Aerospace, Mechanical, Electrical, Software, Systems Engineering, Physics, Mathematics, or Computer Science to design, simulate, and prototype autonomous systems and algorithms.

You will work on guidance, navigation, and control, RF/EO/IR sensors, and multi-disciplinary design optimization within a defense-focused environment.

Qualifications

• Pursuing a PhD in Aerospace, Mechanical, Electrical, Software, Systems Engineering, Physics, Mathematics, or Computer Science.
• Internship or extensive project work in guidance, inertial navigation, modern/adaptive control, or related areas.
• Proficiency in coding practices in Matlab/Simulink, C++, Python or other languages.
• Ability to obtain Interim Secret clearance by start date and ultimately Secret clearance; U.S. citizenship required.
• GPA minimum of 3.0 on a 4.0 scale.

Responsibilities

• Pioneer design and research in guidance, navigation, and control algorithms for full lifecycle development of advanced systems.
• Develop models to simulate and analyze complex physics and sensors.
• Test software and algorithms in embedded systems environments.
• Apply multi-disciplinary optimization techniques for early phase vehicle designs.
• Develop software to support simulation and algorithm development.
• Collaborate with engineers and interact with government sponsors.

Skills

Matlab/Simulink

C++

Python

Education

PhD candidate in STEM fields

Job description

The Johns Hopkins University Applied Physics Laboratory (APL) is seeking PhD candidates in Aerospace, Mechanical, Electrical, Software, Systems Engineering, Physics, Mathematics, or Computer Science to design, simulate, and prototype autonomous systems and algorithms.

You will work on guidance, navigation, and control, RF/EO/IR sensors, and multi-disciplinary design optimization within a defense-focused environment.