University of Southern California

How this program compares

University of Southern California's Online MS in Materials Engineering - Machine Learning lists about $74.6K total tuition — about 74% above the $42.9K AI master's average (87th percentile in our data). It is one of the 54% of programs in our database offered fully or partly online.

Admission Snapshot

Typical admitted student: Applicants typically need a bachelor's degree in materials engineering, mechanical engineering, chemistry, physics, or related field with a strong quantitative background. Prior coursework in programming and mathematics (linear algebra, calculus, differential equations) is strongly preferred.

About This Program

This program combines materials engineering with machine learning to prepare students for data-driven materials discovery and cybermanufacturing. Most students complete it in about 2 years.

Budget planners should note $74.6K estimated total tuition (87th percentile among AI master's programs, above the $42.9K average). Applicants should weigh that premium against the program's outcomes and brand.

It is one of 65 AI-related programs we track in California, of which about 37% offer an online option. On price, it comes in higher than about 75% of the California programs in our data, where typical tuition runs near $63.3K.

Graduates frequently move into roles such as Machine Learning Engineer, with reported salaries around $98,000.

Design and implement machine learning models to predict material properties and optimize material composition.

Career Outcomes

Graduates of University of Southern California's Online MS in Materials Engineering - Machine Learning most often target Machine Learning Engineer roles, where reported compensation runs around $98,000. Its focus on Machine Learning and Deep Learning maps directly to how employers in engineering ai screen for specialized skills rather than generic degrees. Federal projections for this occupational area point to roughly 8% growth this decade — verify the current figure on the BLS Occupational Outlook Handbook before you rely on it.

• 1. Materials Data Scientist
• 2. Computational Materials Engineer
• 3. AI/ML Research Scientist (Materials Industries)
• 4. Product Development Engineer (Advanced Materials)

What You'll Learn

• Design and implement machine learning models to predict material properties and optimize material composition
• Apply deep learning techniques to materials characterization and image analysis
• Develop computational methods for accelerated materials discovery and development
• Integrate domain expertise in materials engineering with advanced data science and AI methodologies

Curriculum Highlights

Core requirements include basics of machine learning for materials, mathematical methods for deep learning, and atomistic simulation of materials.

Top Employers

Top employers include aerospace companies like Boeing and Lockheed Martin, automotive firms like Tesla and General Motors, semiconductor manufacturers like Intel and TSMC, and advanced materials companies like DuPont and 3M.

Admissions

Admission to University of Southern California's Online MS in Materials Engineering - Machine Learning generally expects a ms (master of science). Plan for the GRE, which this program lists as required. Deadlines, testing policies and funding change year to year, so confirm the current requirements on the official program page before applying.

Application Materials

• Statement of Purpose: Required
• Letters of Recommendation: 3
• Resume: Required
• Transcripts: Official transcripts required

Frequently Asked Questions