More than 50 students took part in the Student Poster Competition during the 3rd Annual MIDAS Symposium. The winning entries can be viewed at http://midas.umich.edu/2017-symposium/winning-posters/
The University of Michigan Library system and the Data Acquisition for Data Sciences program (DADS) of the U-M Data Science Initiative (DSI) have recently joined forces to license a major…
Asst. Prof. Emanuel Gull, Physics, is offering a mini-course introducing the Python programming language in a four-lecture series. Beginners without any programming experience as well as programmers who usually use other languages (C, C++,…
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…
A series of training workshops in high performance computing will be held Sept. 21 through Oct. 31, 2017, presented by CSCAR in conjunction with Advanced Research Computing – Technology Services (ARC-TS)….
XSEDE Allocations award eligible users access to compute, visualization, and/or storage resources as well as extended support services. XSEDE has various types of allocations from short term exploratory request to…
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….
Talks from the 2017 MICDE Annual Symposium are now available on the Advanced Research Computing YouTube channel. Due to technical difficulties, the afternoon sessions (Emanuel Gull and J. Tinsley Oden)…
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…
The National Academies Committee on Applied and Theoretical Statistics has released proceedings from its June 2016 workshop titled “Refining the Concept of Scientific Inference When Working with Big Data,” co-chaired…