Summer 2026 - Design DFT/DV Engineer Intern (7410)

TSMCSan Jose, CA
21h$38 - $45

About The Position

Join our dynamic DFT and Verification team at TSMC, where you will play a pivotal role in the development and validation of cutting-edge logic test chips. These chips are instrumental for pioneering yield learning in advanced process nodes and pushing the boundaries of advanced packaging technologies. This internship offers a unique opportunity to tackle complex, real-world challenges at the forefront of semiconductor innovation.   This program is designed for exceptional students currently pursuing a Master’s or Ph.D. degree in Electrical or Computer Engineering, with an expected graduation date in 2026 or 2027. The internship will commence in Summer 2026 and continue through Fall 2026, providing a substantial period for impactful contributions and learning.

Requirements

  • Currently enrolled in a Master’s or Ph.D. program in Electrical Engineering, Computer Engineering, or a closely related field, with an expected graduation date in 2026 or 2027.
  • Demonstrated strong problem-solving abilities and proficiency in programming languages such as Verilog, Python, and TCL.
  • Practical experience utilizing Python for building machine learning models and data analysis.
  • Solid fundamental knowledge of Design-for-Test (DFT) techniques, including ATPG, simulation, logic diagnosis, and Scan compression.

Nice To Haves

  • Familiarity with industry-standard EDA tools such as Synopsys DFT Compiler, Tetramax, and VCS.
  • Research or project experience in defect analysis, fault diagnosis, or testing methodologies for advanced semiconductor technologies (e.g., 3D ICs, chiplet interconnects, novel memory architectures).
  • Exposure to advanced packaging concepts and their implications for test strategies.
  • Experience with SystemVerilog (OOP) and advanced verification methodologies.

Responsibilities

  • Advanced DFT/DV Pattern Simulation & Analysis: Perform block and top-level DFT/DV pattern simulations. Develop and utilize TCL/Verilog monitors to generate comprehensive run-time information, facilitating precise tracking of simulation progress and performance.
  • Automated Defect Insertion & Failure Diagnosis: Implement and execute methodologies for inserting predefined static and dynamic defects/fails. Run simulations to collect detailed fail logs, applying automated clustering techniques to efficiently identify and diagnose the root cause of failures.
  • ATPG & Test Model Explorer Development: Contribute to the development and maintenance of ATPG and test model (STIL/CTL/BSDL/WGL) explorers. This includes modifying and updating test files in response to evolving design changes and specifications.
  • Machine Learning for Simulation Diagnosis: Leverage machine learning and data mining techniques to enhance simulation failure diagnosis, particularly in the context of advanced process nodes. This involves applying cutting-edge analytical methods to complex data sets.
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