Physics-Informed AI Intern

Overview

Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.

Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.

• Formulate physics-informed ML problems in collaboration with RF, EM, circuit, and CAE domain experts.
• Implement PINNs (embedding PDEs as soft/hard constraints), Neural Operators (FNO, DeepONet, GNO) for EM/S-parameter surrogate modeling, and hybrid physics-data models.
• Build fast ML surrogates for CAE workflows — replacing or accelerating FEM, FDTD, and MoM solvers for thermal, structural, and electromagnetic simulation in the design loop.
• Develop GNN-based models for topology-aware physical circuit and transmission line modeling.
• Apply physics-constrained Bayesian optimization, adjoint/gradient methods for differentiable simulators, and RL with physics-based reward shaping.
• Develop scalable pipelines with physics-aware data loaders and benchmark against full-wave EM and CAE reference solvers.

• Pursuing PhD in EE, Applied Math, CS, or related field.
• Strong hands‑on experience with GNNs, Transformers, Vision Models, and generative models.
• Background in Bayesian/numerical optimization and applied RL.
• Proficiency in Python, C++, CUDA; experience with distributed/HPC training.
• Solid software engineering fundamentals (testing, CI/CD, modular design).

• Experience applying ML/RL to physical parameter tuning or design exploration.
• Familiarity with Keysight tools (ADS, RFPro, EMPro, Signal Studio).
• Publications or patents in scientific ML, generative modeling, RL, or optimization.

Candidates who wish to be considered must be enrolled in an accredited college/university as of September 2026. Applicants who have graduated before September 2026 will not be considered unless they are entering or applying to a MS or PhD program after graduating.

Visa Sponsorship is not available for this position. Candidates who now or at any point in the future require sponsorship for employment visa status (e.g., H‑1B Visa status) may not be considered.

California Pay Range: $60.82‑$65.50 per hour

Based on experience, education and skills, most offers will be between the minimum and the midpoint of the salary range listed above.

Note:

For other locations, pay ranges will vary by region.

Careers Privacy Statement. Keysight is an Equal Opportunity Employer.