Graduate Studies in Computational & Data Sciences Info Session – Central Campus

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2016-06-14 11.13.52Learn 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.

Graduate Studies in Computational & Data Sciences Info Session – North Campus

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2016-06-14 11.13.52Learn 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.

Graduate Studies in Computational & Data Sciences Info Session – Central Campus

By |

2016-06-14 11.13.52Learn 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. This year we will offer a new practicum option through the Multidisciplinary Design Program.
  • 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.

Graduate Studies in Computational & Data Sciences Info Session – North Campus

By |

2016-06-14 11.13.52Learn 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. This year we will offer a new practicum option through the Multidisciplinary Design Program.
  • 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.

Graduate programs in computational and data science — informational sessions Sept. 19 & 21

By | Educational, Events, News

Students interested in computational and data science are invited to learn about graduate programs that will prepare them for success in computationally intensive fields. Pizza and pop will be provided.

Two sessions are scheduled:

Monday, Sept. 19, 5 – 6 p.m.
Johnson Rooms, Lurie Engineering Center (North Campus)

Wednesday, Sept. 21, 5 – 6 p.m.
2001 LSA Building (Central Campus)

The sessions will address:

  • The Ph.D. in Scientific Computing, which 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, which 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. This year we will offer a new practicum option through the Multidisciplinary Design Program.
  • The Graduate Certificate in Data Science, which 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.

New graduate course offering: “Methods and Practice of Scientific Computing”

By | Educational, News

The Michigan Institute for Computational Discovery and Engineering (MICDE) is pleased to announce “Methods and Practice of Scientific Computing”, the first graduate course designed and organized by MICDE faculty. The course will be taught in Fall 2016, coordinated by Dr. Brendan Kochunas. This foundational course in scientific computing has been developed as a broad introduction to the subject, and has been designed to support research in all disciplines represented in MICDE. In addition to Brendan Kochunas, the course was developed by MICDE professors Bill Martin, Karthik Duraisamy, Vikram Gavini, and Shravan Veerapaneni, and MICDE Assistant Director Mariana Carrasco-Teja.

The details follow:

NERS 590
4 credits
Prerequisites: Graduate standing and permission of instructor.

This course is designed for graduate students who are developing the methods, and using the tools, of scientific computing in their research. With the increased power and availability of computers to do massively scaled simulations, computational science and engineering as a whole has become an integral part of research that complements experiment and theory. This course will teach students the necessary skills to be effective computational scientists and how to produce work that adheres to the scientific method. A broad range of topics will be covered including: software engineering best practices, computer architectures, computational performance, common algorithms in engineering, solvers, software libraries for scientific computing, uncertainty quantification, verification and validation, and how to use all the various tools to accomplish these things. The class will have lecture twice a week and have an accompanying lab component. Students will be graded on homeworks, lab assignments, and a course project.

A draft of the syllabus can be found here. Please contact MICDE at micde-contact@umich.edu with any questions.

Krishna Garikipati appointed Director of MICDE

By | General Interest, News

Statement from S. Jack Hu, U-M Vice President for Research:

krishnaGarikipatiI’m very pleased to announce that Prof. Krishna Garikipati (Mechanical Engineering and Mathematics) has been appointed the new Director of the Michigan Institute for Computational Discovery and Engineering (MICDE). The Institute has grown significantly since its establishment in 2013 as the interdisciplinary home for the development and use of mathematical algorithms on high performance computers at U-M. Prof. Garikipati has been involved as associate director for research since Fall 2014 and is uniquely positioned to take the institute to the next level.

MICDE is a joint initiative of UMOR, the College of Engineering, and the College of Literature, Science and the Arts. In the past year, it has seen many new and important developments, including the launching of two centers focused on network and storage-enabled collaborative science and data-driven computational physics; new planned course offerings for the PhD in Scientific Computing and the Graduate Certificate in CDE; new initiatives on industrial engagement; and the establishment of the Scientific Computing Student Club. A number of new research initiatives are also being planned, with broadening participation of MICDE-affiliated faculty, whose numbers continue to grow.

Prof. Garikipati will take over the directorship of MICDE from Prof. Eric Michielssen (EECS) who founded the institute in Fall 2013 and served as director, in addition to his role as Associate Vice President for Advanced Research Computing. Prof. Michielssen will continue as AVP.