Help Design the Future of Science. Apply for a Robotics and Instrumentation Internship!

Robotics, artificial intelligence and machine learning are advancing by leaps and bounds, but science labs are still figuring out how to harness these technologies to truly transform science. Argonne has launched the Autonomous Discovery initiative to explore the best ways to apply these technologies to biology, chemistry, and materials sciences.

Our goal is to speed the rate of discovery and bring breakthroughs to the public faster than ever before. We’re looking for motivated undergraduate and graduate students who can bring fresh ideas, diverse perspectives, and creative energy to our team. We want to train people who will work hard, have fun, and help us solve big challenges. Join us in designing the future of science!

About the Internship

Within Argonne’s Autonomous Discovery initiative, the Robotics & Instrumentation Group aims to develop an integrated platform to support artificial intelligence (AI) and robotics-driven instrumentation to transform how scientific experiments are carried out. From discovering novel antimicrobials to cancer drugs to designing novel biomaterials, new types of battery electrolytes, sustainable polymers, and microelectronics, many applications can benefit from the use of AI and robotics.

Interns will:

• Work in our Rapid Prototyping Lab with an interdisciplinary team.
• Develop scalable robotic interfaces and/or artificial intelligence.
• Learn how to integrate diverse robotic platforms and instruments using Python and ROS2.
• Develop and prototype visual analysis toolkits across experimental facilities.
• Provide a poster presentation on their research at the end of their appointment.
• Network with researchers and other cohort interns.

Student Requirements

Students seeking this internship should have the following qualifications:

Required

• Enrolled in an accredited institution pursuing an undergraduate or graduate degree in computer science, robotics, mechanical engineering, electrical engineering, or related disciplines.
• Programming experience in C/C++or Python.
• Minimum GPA of 3.0 on a 4.0 scale.

Preferred

• Programming experience with ROS interfaces.
• Experience with HPC and applied machine learning.