Summer 2025, Intern: Large-scale Graph Analytics (Ph.D. students)

Date Posted:

2024-12-05

Country:

United States of America

Location:

UT13: RC-CT - Corp 411 Silver Lane, East Hartford, CT, 06108 USA

Position Role Type:

Hybrid

RTX Corporation is an Aerospace and Defense company that provides advanced systems and services for commercial, military and government customers worldwide. It comprises three industry-leading businesses – Collins Aerospace Systems, Pratt & Whitney, and Raytheon. Its 185,000 employees enable the company to operate at the edge of known science as they imagine and deliver solutions that push the boundaries in quantum physics, electric propulsion, directed energy, hypersonics, avionics and cybersecurity. The company, formed in 2020 through the combination of Raytheon Company and the United Technologies Corporation aerospace businesses, is headquartered in Arlington, VA. 

To realize our full potential, RTX is committed to creating a company where all employees are respected, valued and supported in the pursuit of their goals. We know companies that embrace diversity in all its forms not only deliver stronger business results, but also become a force for good, fueling stronger business performance and greater opportunity for employees, partners, investors and communities to succeed.

The following position is to join our RTX Technology Research Center (RTRC), AI Systems Engineering team as an intern:

For more than 90 years the RTX Technology Research Center (RTRC) has operated as a multidisciplinary group of experts collaborating on groundbreaking innovations. Our team includes some of the world’s leading scientists, researchers and engineers working to anticipate the discoveries destined to change everything, and they transform that research into the solutions and products that help our businesses shape the future of aerospace and defense. Our unique talent, experience and resources allow us to deliver rapid responses to critical, time-sensitive challenges and develop breakthroughs for a safer, more connected world.

The AI Systems Engineering team researches and develops solutions using model-based systems engineering, formal methods, planning, decision making, controls, machine learning, anomaly detection, computer vision, and failure analysis techniques for a variety of high impact real world problems in the aerospace, manufacturing, and defense industries.

We are looking for a Large Scale Graph Analytics intern to help develop scalable graph-based machine learning models and implement graph structures for large-scale data, incorporating geospatial and behavioral dynamics.

What You Will Do

• Develop scalable graph-based machine learning models and implement graph structures for large-scale data, incorporating geospatial and behavioral dynamics.
• Utilize advanced graph techniques, including deep graph neural networks and hypergraphs, to improve feature representation and graph embeddings for tasks like anomaly detection.
• Optimize algorithms for large datasets using distributed computing or GPU acceleration, and conduct performance experiments against traditional approaches.
• Communicate research findings through presentations, written publications, and support publication in top conferences.
• Collaborate with a focused team on graph neural networks, causal discovery, hardware accelerators, formal methods, model-based design, and deploying AI in safety-critical aerospace and defense systems, gaining exposure to broad AI/ML applications.

What You Will Learn

• Learn about broad areas of AI/ML applications in aerospace and defense within RTX.
• Exposure to industry-standard development processes and tools for executing research projects.
• Improve hands-on technical skills on large-scale data processing and AI/ML development.

Qualifications You Must Have 

• Currently pursuing a Ph.D. in Mathematics, Computer Science, or a related Engineering discipline. Candidates must not graduate prior August 2025. Please submit a copy of your academic transcripts with your application.
• 2+ years of Ph.D. level research experience in broad area of graph neural networks, large scale graph analytics, and machine learning. 
• 2+ years of experience training complex ML pipelines for analytics, graph neural networks for various applications.
• 1+ years of experience of ML software and coding experience in Python, SQL, and familiarity with ML frameworks like PyTorch, Tensorflow.
• 1+ years of experience in analyzing spatiot