About the role
AI summarisedSenior R&D process engineer focused on sustaining and improving ion implantation and rapid thermal annealing processes in a semiconductor cleanroom. The role combines hands-on equipment support with advanced data analytics and AI/ML techniques to ensure stable, high-yield operations and drive continuous improvement.
ResearchOnsiteInstitute of Microelectronics
Key Responsibilities
- Monitor and maintain Implant/RTA performance using SPC, structured analytics, and data-driven fault detection methods
- Develop statistical models or machine learning workflows to predict drift, equipment degradation, or anomalous behaviour
- Build automated dashboards for dose uniformity, activation yield, chamber stability, and thermal cycle repeatability
- Perform DOE studies to identify key parameters impacting junction control, leakage, and defectivity
- Maintain and improve process recipes for dose control, energy accuracy, tilt/twist angles, anneal temperature profiles, and soak times
- Ensure day-to-day process SPC stability, addressing out-of-control conditions and yield-impacting trends
- Lead defect reduction, contamination control, and process recovery after maintenance
- Troubleshoot ion implanter and RTA equipment issues in collaboration with equipment engineers and tool vendors
- Lead improvements for tool stability, beam quality, thermal control accuracy, and wafer-to-wafer repeatability
- Ensure safe handling of high-energy ion beam systems and thermal processing tools in compliance with cleanroom protocols
Requirements
- Bachelor's or Master's degree in Electrical Engineering, Materials Science, Chemical Engineering, Physics, or related fields
- Relevant experience with Ion implantation (high current, medium current, high energy), RTA/RTP systems (spike anneal, soak, millisecond anneal), Basic Epi concepts (dopant incorporation, epi quality, film stress)
- Strong understanding of equipment fundamentals such as vacuum systems, plasma physics (implant), lamp/thermal systems (RTA)
- Proficiency in data analytics (Python, JMP, MATLAB, or similar)
- Exposure to AI/ML-based predictive models for process or equipment monitoring
- Knowledge of SPC, FDC, DOE, and semiconductor manufacturing best practices
- Hands-on cleanroom experience, safety-oriented mindset, and strong problem-solving capabilities