Precision Motion Control Intern

KLA•Milpitas, CA
•Onsite

About The Position

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.

Responsibilities

  • Develop a model-based control framework for a precision motion stage.
  • Build a high-fidelity dynamic model from measured stage performance.
  • Use modern model-based control methods to design a robust controller.
  • Deploy the controller to the stage hardware.
  • Measure the performance of the controller.

Benefits

  • medical
  • dental
  • vision
  • life
  • 401(K) including company matching
  • employee stock purchase program (ESPP)
  • student debt assistance
  • tuition reimbursement program
  • development and career growth opportunities and programs
  • financial planning benefits
  • wellness benefits including an employee assistance program (EAP)
  • paid time off
  • paid company holidays
  • family care and bonding leave
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