Oct 23, 2021  
USC Catalogue 2021-2022 
    
USC Catalogue 2021-2022

Materials Engineering (Machine Learning) (MS)


The Master of Science in Materials Engineering with an emphasis in Machine Learning is for students who have an interest in materials engineering that includes machine learning toward materials discovery, design and processing. U.S. industry and cybermanufacturing are rapidly moving toward data-driven materials discovery and development. Materials engineering combined with machine learning is a novel emerging field that combines materials modeling, simulations and machine learning together into a new paradigm for materials discovery and cybermanufacturing.

Students with a Bachelor of Science in Materials Science, Chemical Engineering, Mechanical Engineering, Civil or Environmental Engineering, Industrial Engineering, Physics and Chemistry, as well as in industry employees who plan to apply machine learning to their research and development, are ideal candidates for the program.

This degree is awarded in conformity with the general requirements of the Viterbi School of Engineering. Students may elect to work for this degree in either the Materials Science or Aerospace and Mechanical Engineering departments. The specific courses that constitute an acceptable program must be approved in advance by the administering department.

A minimum of 20 of the required 28 units should be Materials Science (MASC), Materials Science electives or cross-listed courses. Any course not on the electives list will require department approval to be applied toward the degree.

Graduation requires 28 units total with 3.0 GPA overall.

For admission requirements, refer to Viterbi Graduate Degrees and Requirements .

Engineering Elective Courses (0-8 units)


Students may complete up to 8 units from the following list of non-materials science electives. Up to 8 units total for the degree may be from 400-level courses on approval by department.