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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.
  • 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.
  • 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.

2016-2017 MICDE Research Snapshot

By | Research

2016-2017 has been a year of sustained growth for MICDE’s research portfolio. The number of faculty affiliated with the institute stands at 130, spanning 30 departments and eight schools and colleges. The Center for Scientific Software Infrastructure was established to bring together the U-M community engaged in developing open scientific software. It will focus on establishing best practices for developing, disseminating and documenting scientific software in the public domain. Led by Prof. Emanuel Gull (Physics), the Center aims to provide training and support for researchers that are ready to transform their research codes into well-engineered software. It offers grant support in the form of programmers, consultants, and administrative assistance. It includes a portal to share your code with the research community at large.

MICDE’s two established centers, the Center for Network and Storage-Enabled Collaborative Computational Science (CNSECCS) and the Center for Data-Driven Computational Physics (DaCoP), each held their first symposium, showcasing their first year of research activities. This included evidence of the growing reach of OSiRIS, the open framework for storage, computation and collaboration against big scientific data, and the first results from ConFlux, U-M’s groundbreaking computing cluster for data-driven computational physics. These results have been presented at several conferences, and are appearing in the leading computational journals.

Vorticity field at a late time in the evolution of an elliptic vortex patch computed by a Lagrangian particle method with remeshing and treecode-accelerated evaluation of the Biot-Savart integral. (source: Ling Xu)

MICDE also funded its first round of Catalyst Grants, that are supporting four innovative computational science research projects. Research funded by the Catalyst Grants is breaking new ground, while helping define the future of computational science. This research consists of:

  • studies of the neuronal dynamics of learning and memory formation;
  • new algorithms for the complex, nonlinear dynamics of power grids;
  • novel integral equations methods using recent advances in numerical analysis;  
  • and probabilistic computational frameworks for rare but often catastrophic events.

The past academic year MICDE hosted 14 external speakers with backgrounds and research concentrations that span the breadth of computational science of today and the future. The series culminated in MICDE’s annual symposium: “The New Era of Data-Enabled Computational Science,” which featured talks by worldwide leaders in computational science, including U-M faculty. The symposium included a student poster competition with over 50 entries.

Dr. Ann Almgren from the Lawrence Livermore National Lab speaking about Next Generation AMR, part of the 2016-2017 MICDE Seminar Series

MICDE faculty are committed to growing the already strong U-M community of computational scientists. Over the past year, as before, we have organized a number of workshops to foster collaboration and put together interdisciplinary teams in response to funding calls from federal agencies and foundations.   MICDE offers faculty teams institutional support and direct links to our excellent educational programs as well as cyberinfrastructure, all of which strengthen faculty proposals. With the backing of our parent unit, Advanced Research Computing (ARC), and its technical and consulting services (ARC-Technology Services, and Consulting for Statistics, Computing and Analytics Research), this effort has raised over $22M in external funding over the past 2 years. This includes support from federal agencies (NSF, NIH, and DOD), as well as from industry.  We also work with the academic units at U-M to identify compelling new areas for recruiting the type of faculty members who will drive computational science in the future.

 

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.
  • 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.
  • 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.

MICDE announces 2017-2018 Fellowship recipients

By | Educational, General Interest, Happenings, News

MICDE is pleased to announce the recipients of the 2017-2018 MICDE Fellowships for students enrolled in the PhD in Scientific Computing or the Graduate Certificate in Computational Discovery and Engineering. We had 91 applicants from 25 departments representing 6 schools and colleges. Due to the extraordinary number of high quality applications we increased the number of fellowships from 15 to 20 awards. See our Fellowship page for more information.

AWARDEES

Diksha Dhawan, Chemistry
Negar Farzaneh, Computational Medicine & Bioinformatics
Kritika Iyer, Biomedical Engineering
Tibin John, Neuroscience
Bikash Kanungo, Mechanical Engineering
Yu-Han Kao, Epidemiology
Steven Kiyabu, Mechanical Engineering
Christiana Mavroyiakoumou, Mathematics
Ehsan Mirzakhalili, Mechanical Engineering
Colten Peterson, Climate and Space Sciences & Engineering
James Proctor, Materials Science & Engineering
Evan Rogers, Biomedical Engineering
Longxiu Tian, S. Ross School of Business
Jipu Wang, Nuclear Engineering and Radiological Sciences
Yanming Wang, Chemistry
Zhenlin Wang, Mechanical Engineering
Alicia Welden, Chemistry
Anna White, Industrial & Operations Engineering
Chia-Nan Yeh, Physics
Yiling Zhang, Industrial & Operations Engineering

HONORABLE MENTIONS

Geunyeong Byeon, Industrial & Operations Engineering
Ayoub Gouasmi, Aerospace Engineering
Joseph Kleinhenz, Physics
Jia Li, Physics
Changjiang Liu, Biophysics
Vo Nguyen, Computational Medicine & Bioinformatics
Everardo Olide, Applied Physics
Qiyun Pan, Industrial & Operations Engineering
Pengchuan Wang, Civil & Environmental Engineering
Xinzhu Wei, Ecology & Evolutionary Biology

U-M students invited to apply for MICDE fellowships — May 19 deadline

By | Educational, Funding Opportunities, General Interest, News

University of Michigan students are invited to apply for Michigan Institute for Computational Discovery and Engineering (MICDE) Fellowships for the 2017-2018 academic year. These $4,000 fellowships are available to students in both the Ph.D in Scientific Computing and the Graduate Certificate Program in Computational Discovery and Engineering. Applicants should be graduate students enrolled in either program, although students not yet enrolled but planning to do so may simultaneously submit program and fellowship applications.

Fellows will receive a $4,000 research fund that can be used to attend a conference, to buy a computer, or for any other approved activity that enhances the Fellow’s graduate experience. We also ask that Fellows attend at least 8 MICDE seminars between Fall 2017 and Winter 2018, attend one MICDE students’ networking event, and present a poster at the MICDE Symposium on March 22, 2018. For more details and to apply please visit http://micde.umich.edu/academic-programs/micde-fellowships/.

Interested students should download and complete the application form, and submit it with a one-page resume as a SINGLE PDF DOCUMENT to MICDE-apps@umich.edu. The due date for applications is May 19, 2017, 5:00 E.T. We expect to announce the awardees onJune 5, 2017.

We encourage applications from all qualified candidates, including women and minorities.