Course Overview!

The PhD in Engineering with an Applied Data Science Specialization at Cleveland State University, in collaboration with the Cleveland Clinic's Lerner Research Institute, offers a unique opportunity for doctoral candidates to conduct cutting-edge research in biomedical data science and informatics, focusing on solving problems in biology, medicine, and public health. The program emphasizes the practical applications of computer science and data science principles in medical settings, along with high-performance computing and ethical considerations around using AI within healthcare. Students benefit from access to substantial funding, state-of-the-art equipment, and the collaboration between university and clinic researchers. The program aims to train leaders who can apply creative solutions to challenging technological problems.

Course Structure

The PhD program requires a minimum of 90 credits beyond the bachelor's degree, which include at least 40 credits of coursework and 30 credits of research. Coursework includes advanced engineering mathematics (minimum 6 credits), graduate-level courses from outside engineering (minimum 6 credits), a research communications course (minimum 3 credits), a doctoral seminar, and specialization-specific courses in applied data science. Specialization requirements include core courses like Analysis of Algorithms, Artificial Intelligence, Bioinformatics and Applied Regression Models, alongside electives across biomedical engineering, computer science, and statistics. A substantial portion of the program focuses on dissertation research, requiring successful completion of qualifying and candidacy exams, a comprehensive dissertation, and publication in a peer-reviewed journal before the final defense.