Physics AI Internship (Summer 2027)

Date posted 10/29/2026

Category Interns/Temp Hire Type Intern Job ID 19536 Base Salary Range $0-$0 Remote Eligible Yes Date Posted 10/29/2026

We Are

Drive technology innovations that shape the way we live and connect. Our technology drives the Era of Pervasive Intelligence, where smart tech and AI are seamlessly woven into daily life. From self-driving cars and health-monitoring smartwatches to renewable energy systems that efficiently distribute clean power, Synopsys creates high-performance silicon chips that help build a healthier, safer, and more sustainable world.

Internship Experience

At Synopsys, interns dive into real-world projects, gaining hands-on experience while collaborating with our passionate teams worldwide-and having fun in the process! You''ll have the freedom to share your ideas, unleash your creativity, and explore your interests. This is your opportunity to bring your solutions to life and work with cutting-edge technology that shapes not only the future of innovation but also your own career path. Join us and start shaping your future today!

Mission Statement

Our mission is to fuel today's innovations and spark tomorrow's creativity. Together, we embrace a growth mindset, empower one another, and collaborate to achieve our shared goals. Every day, we live by our values of Integrity, Excellence, Leadership, and Passion, fostering an inclusive culture where everyone can thrive-both at work and beyond.

What You'll Be Doing

• Engage in cutting-edge research at the intersection of deep learning, scientific computing, and foundation models for physics applications.
• Contribute to the development of Large Physics Foundation Models (LPFMs) by exploring novel architectures and innovative training strategies.
• Build and curate large-scale physics datasets, and design the infrastructure needed to support data-driven AI research in the physical sciences.
• Collaborate closely with cross-functional teams of researchers and engineers, sharing your ideas and learning from leading experts in the field.
• Present findings, participate in knowledge-sharing sessions, and help shape the direction of AI for the physical sciences.

What You'll Need

• Currently pursuing a Master''s or PhD degree in Physics, Computer Science, Engineering, or a related field.
• Strong passion for applying AI and deep learning to scientific or physics-based problems.
• Experience with scientific computing, machine learning frameworks, and large-scale data management.
• Excellent problem-solving, communication, and collaboration skills.
• Self-motivated, creative, and eager to contribute to high-impact research and engineering projects.

Key Program Facts:

• Program Length: 3-4 months
• Location: Sunnyvale, California, United States
• Working Model: In-office, hybrid or remote
• Full-Time/Part-Time: Full-time
• Start Date: May / June 2027

Equal Opportunity Statement

Synopsys is committed to creating an inclusive workplace and is an equal opportunity employer. We welcome all qualified applicants to apply, regardless of age, color, family or medical leave, gender identity or expression, marital status, disability, race and ethnicity, religion, sexual orientation, or any other characteristic protected by local laws. If you need assistance or a reasonable accommodation during the application process, please reach out to us.

At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.

In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a competitive total rewards package. The actual compensation offered will be based on a number of job-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request. The base salary range for this role is across the U.S.