Quantum EM Solver Intern

Overview

In this role, you will be an intern in a  R&D team developing simulation and design solutions for the emerging quantum technology market. The work combines microwave circuit design, computational electromagnetics, quantum-device modeling, and scientific software development. Working within an Agile development team and with guidance from experienced engineers, you will contribute to EM solver  software. The ideal intern takes a proactive approach, learns quickly, and is willing to "roll up their sleeves" to solve challenging technical problems.

Keysight is a mission-critical design enablement partner for organizations solving the world’s most complex engineering challenges. With deep engineering expertise and leading design, emulation, and test solutions, our ~16,800 employees help customers in over 100 countries accelerate innovation across communications, automotive, energy, quantum, aerospace and defense, semiconductor, and artificial intelligence markets. Learn more about what we do.

At Keysight, people come together to explore new ideas, challenge what's possible, and advance the technologies defining the future. Here, you'll find opportunities to do your best work, take your career further, and thrive in an award-winningculture.Learn more about our benefits.

Responsibilities

• Develop computational EM workflows that connect layout, electromagnetic simulation, microwave circuit simulation, and system-level analysis using tools such as ADS, RFPro, EMPro, HFSS, CST, COMSOL, Momentum, or Sonnet.
• Apply graduate-level knowledge of electromagnetic field theory and numerical methods to investigate modeling challenges involving Maxwell's equations, meshing, boundary conditions, eigenmodes, parameter extraction, or multi-scale structures.
• Evaluate simulation accuracy by comparing results with analytical models, published results, measurement data, or results from established simulation tools.
• Collaborate with computational EM, quantum, RF/microwave, circuit simulation, and software engineering teams to translate research ideas and workflow needs into reusable capabilities.
• Produce clear technical documentation, validation examples, and presentations that communicate methods, results, assumptions, and limitations.

Qualifications

Required

• Currently pursuing a Master's or Ph.D. degree in Electrical Engineering, Physics, Applied Mathematics, Computer Science, or a related technical discipline.
• Graduate coursework, research, or project experience in one or more of the following: computational electromagnetics, electromagnetic simulation, numerical methods, RF/microwave engineering, quantum engineering, or scientific computing.
• Experience modeling electromagnetic structures or microwave circuits with at least one relevant simulation environment, such as ADS, EMPro, RFPro, Momentum, HFSS, CST, COMSOL, or Sonnet.
• Working knowledge of electromagnetic field theory and familiarity with numerical simulation concepts such as FEM, MoM, FDTD, eigenvalue or eigenmode analysis, meshing, sparse linear algebra, or boundary conditions.
• Experience using Python for scientific computing, data analysis, automation, or software development.
• Ability to formulate a technical problem, evaluate results critically, and document conclusions with appropriate validation.
• Ability to work effectively in a multi-site, multidisciplinary, and multicultural team environment.
• Ability to quickly learn new technologies and contribute within an Agile software development process.

Desired

• Research or project experience applying computational EM to superconducting circuits, quantum processors, resonators, couplers, cryogenic microwave systems, advanced packaging, or high-frequency interconnects.
• Experience developing or validating workflows that span layout, EM simulation, circuit simulation, and system-level analysis.
• Experience with C++ and an understanding of software development practices, testing, version control, and software architecture.
• Exposure to parallel computing, HPC environments, sparse matrix solvers, reduced-order modeling, surrogate modeling, parameter extraction, or model generation.
• Familiarity with multi-physics simulation involving thermal, mechanical, material, or quantum effects.
• Basic understanding of electronic design automation products, engineering test solutions, and the needs of research or commercial engineering users.

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