Summer 2026 - Physics AI Intern (Hybrid)

RTX • East Hartford, CT

18h • Hybrid

About The Position

The Advanced Learning and Analytics team researches and develops machine learning, computer vision, reinforcement learning, large language models and human computer interaction solutions for a variety of high impact real world problems in the aerospace, manufacturing and defense industries. Examples include autonomy, multi-agent coordination, cybersecurity, material discovery and design. We conduct basic and applied research in a stimulating multi-disciplinary environment where scientists, engineers, practitioners, and subject matter experts collaborate and exchange experience. We are looking for summer interns to support research on the broad topic of Physics AI which can be implemented to accelerate the modeling and design of complex engineering systems in aerospace domain.

Requirements

• Currently pursuing a Ph.D. in Computer Science, Mathematics, or a related Engineering discipline with a focus on physics AI.
• Candidates must not graduate before December 2026.
• A copy of your academic transcripts must be submitted with your application.
• At least 1 year of Ph.D.-level research experience in the broad field of physics AI.
• At least 1 year of machine learning software development experience in Python, with proficiency in deep learning frameworks such as PyTorch or TensorFlow.
• Familiarity with simulation tools such as ANSYS, COMSOL, or similar platforms.
• Must be authorized to work in the U.S. without sponsorship now or in the future. RTX does not offer sponsorship for this position.

Nice To Haves

• A publication record in top AI and SciML venues such as NeurIPS, ICML, ICLR, SIAM, or AAAI.
• Proven ability to set research direction, work independently, and contribute effectively to collaborative team efforts.

Responsibilities

• Develop algorithms, implement software, and train models for novel Physics-Informed Machine Learning (PIML) or Scientific Machine Learning (SciML) architectures.
• Incorporate physics into deep learning architectures in a semi-intrusive manner when partial physics models are available.
• Demonstrate the use of PIML to learn spatiotemporal fields from sparse data.
• Implement and operationalize PIML/SciML systems autonomously using agentic AI.
• Design and conduct experiments on GPU clusters, benchmarking performance against established baselines.
• Present research findings through presentations, technical reports, and contributions to top-tier publications.
• Collaborate with a focused team to develop advanced physics AI tools.

Benefits

• Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays.
• Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement.
• Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement.
• Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company’s performance.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: Ph.D. or professional degree