Materials Engineering (Machine Learning) (MS) at University of Southern California

The MS in Materials Engineering with an emphasis in Machine Learning is for students interested in applying machine learning to materials discovery, design and processing, combining materials modeling, simulation and machine learning for data-driven materials discovery and cybermanufacturing. Students may work toward the degree in either the Materials Science or Aerospace and Mechanical Engineering department.

Faculty: Viterbi School of Engineering  |  Department: Materials Science or Aerospace and Mechanical Engineering  |  Duration: 28 units  |  Study mode: full-time  |  Location: Los Angeles, CA, United States

What you will study

Core courses (12 units) are MASC 515 Machine Learning in Materials, Chemical and Energy Engineering, MASC 520 Mathematical Methods for Deep Learning and MASC 575 Basics of Atomistic Simulation of Materials, plus an ENGR 595 practicum, 8-16 units of materials science electives and 0-8 units of engineering electives. At least 20 of the 28 units must be MASC, materials science electives or cross-listed courses.

Career pathways

Applying machine learning to research and development in materials and cybermanufacturing.

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