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This position is in the Logic Technology Development team working in one of the most advanced semiconductor cleanroom facilities in the world. You will be designing, executing, and analyzing experiments necessary to meet engineering specifications for their process.What we do:
Set advanced device performance targets for Process Design Kit releases and Interface with Design and Foundry partners to address circuit-level issues.
Assess Silicon-to-Simulation health and readiness for High Volume Manufacturing.
Define robust test structures and test programs to validate advanced design rules and reliably extract key device parameters.
Use Statistics, Data Mining, and other data analysis techniques to collect, explore, and extract insights from Electrical-test, yield, and fab data to define future development direction.
You must possess the minimum qualifications below to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. The experience listed below would be obtained through a combination of your schoolwork/classes/ experimental research and/or relevant previous job and/or internship experiences.
Minimum Qualifications
Must possess a master's degree with 5+ years semiconductor industry experiences or Ph.D. degree in electrical engineering (EE), electrical and computer engineering (ECE), electrical engineering and computer science (EECS) directly related to Semiconductor field.
Minimum of 6 months of experience in one or more of the following: Semiconductor materials, fabrication, and device physics, Electrical characterization of Semiconductor Devices (transistor, diode, etc.)
Preferred Qualifications
Advanced Transistor Device Structures and Device Physics.
Process monitoring Test structures design and layout experience.
Device and circuit simulation.
Statistical Process Control (SPC) or Design of Experiments (DOE) principles and engineering analysis tools.
Expertise in database structures, research methods, machine learning, analytics packages (i.e., JMP, MATLAB, Octave), scripting languages (i.e., Python, JSL, Perl, TCL), or programming languages (i.e., SQL, C/C++)
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