Precision Motion Control Intern

KLA•Milpitas, CA

4d•Onsite

About The Position

The Semiconductor Products and Customers (Semi PC) business unit designs, builds and sells KLA’s product portfolio to help chip manufacturers meet high-quality standards for technologies like AI, data centers, automotive and electronic devices. Our inspection, metrology, and analytics systems detect and monitor defects across logic and memory chips, specialty semiconductors, wafers, reticles, advanced packaging, process equipment and materials. We also develop technologies for specialty processes, IC substrates, and PCB manufacturing, including etch and deposition, component inspection, and imaging and analytics. The RAPID division leads the industry in reticle inspection solutions, helping ensure high lithography yields and cost-effective semiconductor manufacturing. Its systems support both mask shops and fabs by detecting defects early in the process, enabling faster, more reliable production. In this role, you will play a key part in advancing business priorities by delivering high-impact work across your area of expertise. The Mechatronics team in KLA's RAPID Division is looking for an intern to develop a model-based control framework for a precision motion stage. In this project, the intern will build a high-fidelity dynamic model from measured stage performance. The intern will then use modern model-based control methods to design a robust controller, deploy it to the stage hardware, and measure its performance.

Requirements

Currently enrolled in an MS or PhD program in Mechanical Engineering, Electrical Engineering, or a related field.
Coursework or project experience in feedback control systems, including frequency-domain analysis (Bode and Nyquist plots, stability margins).
Understanding of dynamic system modeling, transfer functions and state-space representations.
Skill in MATLAB and/or Simulink for modeling, analysis and control design.
Hands-on lab experience running experiments and analyzing measured data.
Strong written and spoken communication skills, including documenting and presenting technical results.

Nice To Haves

Pursuing an MS or PhD with a focus on control systems, mechatronics or precision motion control.
Experience with frequency-domain loop shaping and robust control synthesis (e.g., H∞; μ-synthesis).
Experience with system identification and fitting models to measured FRF data.
Familiarity with multivariable (MIMO) systems, modal analysis and cross-axis coupling.
Knowledge of practical controller implementation, including feedforward design, notch and loop-shaping filters, discretization and real-time embedded control.
Experience with FRF measurement tools, such as dynamic signal analyzers or swept-sine and noise-based excitation.
Experience with Python for data analysis.
Experience designing structured test plans and comparing controller performance against a baseline.