Cadence plays a critical role in creating the technologies that modern life depends on. We are a global electronic design automation company, providing software, hardware, and intellectual property to design advanced semiconductor chips that enable our customers create revolutionary products and experiences.

Thanks to the outstanding caliber of the Cadence team and the empowering culture that we have cultivated for over 25 years, Cadence continues to be recognized by Fortune Magazine as one of the 100 Best Companies to Work For. Our shared passion for solving the world’s toughest technical challenges, our dedication to pushing the limits of the industry, and our drive to do meaningful work differentiates the people of Cadence.

Cadence is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, basis of disability, or any other protected class.

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

This internship will focus on using machine learning algorithms in thermal optimization application.

You will have the opportunity to help design, develop, troubleshoot and debug PCB/package/chip thermal analysis software.

Works on extremely complex problems where analysis of situations or data requires an evaluation of intangible variance factors.

Exercises independent judgment in developing methods, techniques, and evaluation criterion for obtaining results.

Work leadership may be provided by assigning work and resolving problems.
Position Requirements:
• Currently pursuing PhD degree in ME/EE/CS or other related engineering discipline, have strong programming skills in C++, and deep familiarity with object-oriented programming methods.
• Prior knowledge and experience with distributed/multi-threaded programming, numerical analysis techniques, meshing techniques, finite-element based thermal simulation, CFD analysis, and in-depth understanding of electric cooling of PCB/package/chip preferred.
• Experience on automatic design optimization for thermal targets is a plus.

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