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Responsibilities include, but are not limited to:

- Develop, enhance, and maintain compact models for CMOS, BJT, and LDMOS devices.
- Create semiconductor device compact models for SPICE simulators.
- Validate and correlate compact models against measured device data.
- Debug and resolve convergence challenges encountered during circuit simulations.
- Develop deep‑learning–based methods for parameter extraction and optimization.
- Apply machine learning workflows to accelerate the parameter‑extraction process.
- Build scripting tools to automate extraction tasks and generate reports.
- Produce comprehensive reports summarizing project results and findings.

Minimum Qualifications

- Ph.D. in Semiconductor Device Physics, Characterization, Modeling, or a related field.
- Skilled in optimization algorithms,



data correlation, and automated extraction processes.
- Strong analytical skills, execution mindset, and sense of urgency
- Ability to collaborate across process, modeling, and PDK teams

Preferred Qualifications

- Experience with semiconductor device characterization and measurement techniques.
- Experience with Python and Verilog-A programming
- Experience developing deep-learning, neural-network, and scientific machine-learning solutions using contemporary frameworks such as PyTorch, Tensor Flow, or JAX.
Job Req Type: Experienced Required Travel: Yes, 10% of the time Shift Type: 1st Shift/Days

📌 Senior Engineer, Research Science Engineering (India)
🏢 Analog Devices
📍 India