Learn about graduate programs that will prepare you for success in computationally intensive fields — **pizza and pop provided**

- The Ph.D. in Scientific Computing is open to all Ph.D. students who will make extensive use of large-scale computation, computational methods, or algorithms for advanced computer architectures in their studies. It is a joint degree program, with students earning a Ph.D. from their current departments, “… and Scientific Computing” — for example, “Ph.D. in Aerospace Engineering and Scientific Computing.”
- The Graduate Certificate in Computational Discovery and Engineering trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan.
- The Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:

1) Modeling — Understanding of core data science principles, assumptions and applications;

2) Technology — Knowledge of basic protocols for data management, processing, computation, information extraction, and visualization;

3) Practice — Hands-on experience with real data, modeling tools, and technology resources. - The Graduate Certificate in Computational Neuroscience provides training in interdisciplinary computational neuroscience to graduate students in experimental neuroscience programs and to graduate students in quantitative science programs, such as physics, biophysics, mathematics and engineering. The curriculum includes required core computational neuroscience courses and coursework outside of the student’s home department research focus, i.e. quantitative coursework for students in experimental programs, and neuroscience coursework for students in quantitative programs.