VIP Projects: CCI Automotive Cybersecurity Team

Goals

The purpose of the Raytheon Fellowship Program is to cultivate a cleared student pipeline in the areas of cybersecurity and machine learning. The RFP is a 3-year cohort-based program that engages students in their sophomore through senior years, providing hands-on experience with the Linux-based foundations (year 1), open-source cybersecurity and machine learning tools (year 2), and project-specific specializations and topics at various restricted levels (year 3) to help the student hit the ground running when they start their careers as a cleared developed at Raytheon Technologies.

An important characteristic of the fellowship is that it follows a scholarship-for-service model, representing mutual commitment of both the student and the sponsor. Target enrollment for year 1 of each cohort is 20 students, with Raytheon providing summer internships to all qualifying students. Following the internship, high performing students will be offered full-time positions at Raytheon upon graduation (with a two-year service commitment) and then continue into years 2 and 3 of the program.

Issues Involved or Addressed

• Unique challenges associated with Linux-based software, algorithm, and cyber technique development to support cyber defense, cyber operations, and multi-modal machine learning applications.
• Software development tools (open-source and custom) and DevOps topics.
• A wide variety of ITAR-level examples and use cases for application of cyber and ML technologies.
• Note: given the program requirements, all student participants must be U.S. citizens and capable of meeting requirements for a security clearance.

Methods and Technologies

• RFP fellows meet in a hybrid class-/lab-like atmosphere twice per week, and are taught hands-on cyber and ML techniques, with weekly assignments to self-validate progress and understanding.
• Students should expect an 8-10 hour/week commitment as part of the program.
• Students will be taught a variety of languages and tools:
  • Linux-based development
  • Python, C, and C++
  • Computer Networking
  • Keras, TensorFlow, PyTorch
  • Cybersecurity Attacks

Academic Majors of Interest

• Computer Science
• Computer Engineering
• Computational Modeling and Data Analytics
• Electrical and Computer Engineering
• Other students with similar experience seeking future developer roles

Preferred Interests and Preparation

• Commitment to learning and practicing new computing techniques
• Previous Linux-based SW development
• Previous algorithm development, particularly in low-level languages
• Experience with hobbyist computing platforms and/or hardware

Team Advisors