Job Description

Locations

• Taiwan, Taichung - Fab 16

Skills Required

• semiconductor process engineeringintermediate
• process defect root cause analysisintermediate
• processintermediate
• yield modelingintermediate
• semiconductor manufacturing change managementintermediate

Required Qualifications

• Master’s degree in Engineering (Semiconductor, Materials, Chemical, Mechanical, Electrical, Physics) or related field. (degree in engineering)
• Hands-on experience in semiconductor process engineering, yield engineering, defect analysis, or simulation-related roles. (experience)
• Strong analytical mindset with proven experience in process defect root cause analysis. (experience)
• Ability to analyze and interpret manufacturing and process data (inline, metrology, defect, yield) and translate results into clear technical conclusions. (experience)
• Strong communication skills with the ability to explain complex simulation results and physical insights to cross-functional engineering teams. (experience)
• Master’s degree in Engineering (Semiconductor, Materials, Chemical, Mechanical, Electrical, Physics) or related field. (degree in engineering)
• Hands-on experience in semiconductor process engineering, yield engineering, defect analysis, or simulation-related roles. (experience)
• Strong analytical mindset with proven experience in process defect root cause analysis. (experience)
• Ability to analyze and interpret manufacturing and process data (inline, metrology, defect, yield) and translate results into clear technical conclusions. (experience)
• Strong communication skills with the ability to explain complex simulation results and physical insights to cross-functional engineering teams. (experience)

Preferred Qualifications

• PhD or advanced Master’s degree in Engineering, Physics, or a related discipline. (degree in advanced master)
• Experience with process, defect, or physical modeling and simulation tools (e.g., TCAD, process simulation, statistical modeling, or custom-built models). (experience)
• Familiarity with yield modeling, defect density analysis, and process window optimization methodologies. (experience)
• Experience integrating simulation outputs with SPC, inline metrology, defect inspection, or yield analysis data. (experience)
• Demonstrated track record of successfully applying simulation or analytical approaches to deliver measurable defect reduction or yield improvement. (experience)
• Knowledge of semiconductor manufacturing change management, risk assessment, and internal or customer audit requirements. (experience)
• PhD or advanced Master’s degree in Engineering, Physics, or a related discipline. (degree in advanced master)
• Experience with process, defect, or physical modeling and simulation tools (e.g., TCAD, process simulation, statistical modeling, or custom-built models). (experience)
• Familiarity with yield modeling, defect density analysis, and process window optimization methodologies. (experience)
• Experience integrating simulation outputs with SPC, inline metrology, defect inspection, or yield analysis data. (experience)
• Demonstrated track record of successfully applying simulation or analytical approaches to deliver measurable defect reduction or yield improvement. (experience)
• Knowledge of semiconductor manufacturing change management, risk assessment, and internal or customer audit requirements. (experience)

Responsibilities

• Develop and apply process / defect simulation models to understand defect generation mechanisms across key wafer fabrication steps.
• Correlate simulation results with inline defect, EBI, process data, and yield indicators to identify true root causes of defects.
• Drive data-backed process optimization strategies to expand process windows and improve yield and reliability.
• Perform what-if simulations to evaluate the impact of process parameter changes, material variations, or equipment conditions.
• Partner with process, integration, and equipment engineers to translate simulation insights into fab-implementable actions.
• Lead or support defect reduction, yield improvement, and cost reduction projects using structured problem-solving methodologies (FA, FMEA, DOE, SPC, 8D).
• Support new process introduction (NPI) and baseline qualification by assessing defect risks through modeling and simulation.
• Document models, assumptions, and results; continuously improve simulation methodologies and best practices.
• Develop and apply process / defect simulation models to understand defect generation mechanisms across key wafer fabrication steps.
• Correlate simulation results with inline defect, EBI, process data, and yield indicators to identify true root causes of defects.
• Drive data-backed process optimization strategies to expand process windows and improve yield and reliability.
• Perform what-if simulations to evaluate the impact of process parameter changes, material variations, or equipment conditions.
• Partner with process, integration, and equipment engineers to translate simulation insights into fab-implementable actions.
• Lead or support defect reduction, yield improvement, and cost reduction projects using structured problem-solving methodologies (FA, FMEA, DOE, SPC, 8D).
• Support new process introduction (NPI) and baseline qualification by assessing defect risks through modeling and simulation.
• Document models, assumptions, and results; continuously improve simulation methodologies and best practices.
• - Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements.
• - Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.
• - Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business

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