We Are
At Synopsys, we lead innovation in electronic design automation and semiconductor technology. Our TCAD solutions enable accurate physics-based device and process simulation for advanced semiconductor technologies. Increasingly, AI-driven methodologies and Python-based automation are transforming how simulation workflows are developed, validated, released, and scaled.
You Are
You are a technically strong and curious engineer with a solid background in TCAD and semiconductor device physics, combined with a passion for Python-based engineering automation and applied AI/ML. You enjoy working at the intersection of physics-driven simulation, data-assisted modeling, software infrastructure, and engineering productivity.
What You’ll Be Doing
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Develop, enhance, and maintain TCAD simulation workflows for device and/or process modeling across advanced semiconductor technologies.
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Drive improvements in device physics models, process flows, and simulation engines through hands-on analysis, benchmarking, and close collaboration with core R&D teams.
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Design and implement Python-based tools, APIs, and automation frameworks to improve workflow robustness, usability, and scalability.
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Use AI and Python-based approaches to improve the efficiency, quality, and automation of the TCAD release process, including regression analysis, validation flows, and release readiness metrics.
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Collaborate with cross-functional teams to translate engineering requirements into production-quality software solutions.
The Impact You Will Have
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You will directly influence the next generation of TCAD tools by improving simulation accuracy, performance, and usability through AI-driven innovation and Python automation.
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Enable more robust and efficient TCAD releases using data-driven validation and automated regression workflows.
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Influence the evolution of TCAD tools toward modern, scalable, AI-enhanced platforms.
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Accelerate adoption of advanced TCAD capabilities across internal teams and customers.
What You’ll Need
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MS or PhD in Electrical Engineering, Physics, Materials Science, Computer Science, or equivalent.
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5+ years of industry experience in TCAD, semiconductor device physics, or process simulation.
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Strong proficiency in Python for scientific computing, automation, and tooling.
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Experience applying AI/ML techniques to engineering workflows.
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Strong analytical thinking, problem-solving ability, and communication skills.
Nice to Have
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Experience applying ML frameworks to scientific or engineering problems.
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Exposure to EDA tool development or semiconductor R&D environments.
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Experience supporting large-scale validation or release processes.
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You can sit with a device physicist discussing threshold voltage roll-off and walk out with a Python script that automates the entire calibration sweep by end of week
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You are comfortable working in ambiguity, whether that means incomplete specs, noisy data, or a simulation deck that crashes for reasons no one understands yet
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You have a point of view on what good automation looks like and you push back when a workflow is too brittle, too manual, or too hard for the next engineer to maintain
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You think about the downstream impact of your work, not just whether the simulation converges but whether the release process will break when someone runs it on a different machine
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You are curious about new methods and willing to experiment, but pragmatic enough to know when a simple Python loop beats a fancy neural network
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You communicate clearly across disciplines, translating between physics language, software engineering language, and business priorities without losing the thread
The Team You’ll Be A Part Of
You will join a highly skilled TCAD team advancing simulation technology through physics-based models and AI-enhanced methodologies, working closely with product development, applications, and research teams worldwide.
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