Imaging Systems Intern — AI, Optics & Embedded HW

The Johns Hopkins University Applied Physics Laboratory; Laurel (MD); On-site; USD 30,000 - 66,000; Full time

Job summary

The Johns Hopkins University Applied Physics Laboratory’s Imaging Systems Group seeks interns to model, analyze data, prototype hardware, and develop AI/ML- based imaging solutions. You will work with optical sensors, embedded hardware, and test benches in a collaborative environment touching defense, remote sensing, and science applications.

Ideal candidates are pursuing degrees in engineering or CS with hands-on lab experience, strong programming skills, and an interest in signal processing,

Qualifications

• Pursuing a Bachelor's, Master's or PhD in Computer/Electrical/Mechanical Engineering, CS, Physics, or Optical Science.
• Minimum 3.0 GPA on a 4.0 scale.
• Ability to work independently and in multidisciplinary teams with strong communication skills.
• Ability to translate and analyze data and report findings clearly in writing or visuals.
• Ability to read technical docs and use debugging tools with Git repositories.

Responsibilities

• Develop, evaluate, and deploy imaging system hardware, algorithms, or software.
• Assist in brainstorming and developing new optical imaging initiatives through R&D.
• Document technical contributions and present findings in forums.
• Support field integration and testing of developed systems.
• Develop GUI interfaces for sensor integration over serial/TCP/IP and integrate embedded systems (e.g., NVIDIA Jetson).

Skills

C/C++

Python

MATLAB

JAVA

Typescript

C#

Education

Pursuing Bachelor's/Master's/PhD in Computer Engineering, Electrical/Mechanical Engineering, Computer Science, Physics or Optical Science

Tools

Linux

GPU

Docker

TensorFlow

FPGA

GitHub/GitLab

Job description

The Johns Hopkins University Applied Physics Laboratory’s Imaging Systems Group seeks interns to model, analyze data, prototype hardware, and develop AI/ML- based imaging solutions. You will work with optical sensors, embedded hardware, and test benches in a collaborative environment touching defense, remote sensing, and science applications.

Ideal candidates are pursuing degrees in engineering or CS with hands-on lab experience, strong programming skills, and an interest in signal processing,