Manufacturing, Yield & Technology Transfer
Facilitate process improvements and corrective actions for yield, reliability, and manufacturability issues using root-cause analysis and data mining and analysis.
Support Process Engineering and Yield Engineering teams to improve process quality and yield for technologies released to manufacturing.
Enable smooth technology transfers into and out of the fab by using data-driven monitoring, excursion detection, and learning systems.
Required
MS or PhD in Electrical Engineering, Physics, Chemistry, Chemical Engineering, Materials Engineering, or related technical field.
Minimum of 10 years’ experience in semiconductor manufacturing or process development or process integration in a semiconductor manufacturing environment.
Knowledge of semiconductor processes such as oxidation, implant, deposition (CVD, PECVD, etc.), RIE, CMP, Lithography used in FEOL and BEOL wafer fabrication.
Experience applying DOE, statistical analysis, and data analytics to semiconductor development.
Understanding of semiconductor device physics and construction, including CMOS, DMOS, Bipolar, and Trench FET devices.
Strong written and verbal communication skills with the ability to convey complex technical concepts clearly.
Proven problem-solving ability and strong collaboration skills in cross-functional teams.
Preferred
Experience with 180 nm through 40 nm technologies.
Knowledge of intrinsic reliability testing methodologies, including GOI, VRamp, TDDB, HCI, EM, and SM.
Hands-on experience with process and device TCAD simulations.
Experience designing and evaluating physical and electrical design rule test structures.
Familiarity with AI/ML techniques, data mining, or statistical modeling applied to semiconductor process or device data.
Experience using scripting languages (e.g., Python, MATLAB, JMP, or equivalent) for data analysis, automation, or model development.