Semiconductor Device Modeling Engineer

Intel Intel · Semiconductors · Oregon, Hillsboro, United States +1

Seeking a Semiconductor Device Modeling Engineer to support compact modeling activities for Intel's new technologies. Responsibilities include supporting compact modeling, developing methodologies for device targeting, and potentially applying machine learning algorithms to data analysis and model development.

What you'd actually do

  1. As a semiconductor device modeling engineer, you will be playing a key role to support compact modeling activities for Intel's new technologies.
  2. Development of methodologies for device targeting (e.g., transistors) and benchmarking circuits (e.g., ring oscillators), including corners and statistical variation models.
  3. Experience with machine learning algorithms and their application is data analysis and compact model development.

Skills

Required

  • Bachelor's degree in Electrical Engineering or related discipline and 5+ years of industry experience in the semiconductor field; or Master's degree in Electrical Engineering or related discipline and at least 3 years of industry experience in the semiconductor field; or Ph.D. in Electrical Engineering or related discipline.
  • Graduate coursework or research experience in semiconductor device physics or 5+ years of work experience in Semiconductor device physics.
  • 1+ years' experience Python scripting for data analysis, automation and documentation.

Nice to have

  • Ph.D. in Electrical Engineering or a related discipline with 3+ years of industry experience in the semiconductor field.
  • Proficiency with extraction tools (e.g., ICCAP, MBP) and commercial simulators such as HSPICE, Spectre, etc.
  • Hands-on experience with BSIM-CMG and other compact models for transistor modeling at advanced nodes (e.g., FinFET, GAA) including experience in one or more of the following areas: Experience developing Layout-dependent effects (LDE) for FinFET or GAAFET technologies and their impact on circuit performance.
  • Development of methodologies for device targeting (e.g., transistors) and benchmarking circuits (e.g., ring oscillators), including corners and statistical variation models.
  • Modeling using Open Model Interface (OMI).
  • Strong understanding of process flow, layout, and basic circuit design/simulation.
  • Modeling self-heating effects and their influence on device and circuit performance.
  • Proven capability to collaborate across multiple teams and geographies.
  • Experience with machine learning algorithms and their application is data analysis and compact model development.