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Center of Excellence in Bioinformatics building

The Center for Computational Research (CCR), a leading academic supercomputing facility, maintains a high-performance computing environment, high-end visualization laboratories, and support staff with expertise in computing, visualization, and networking.  

The mission of the Center for Computational Research (CCR) is to:
A leading academic supercomputing facility, CCR has more than 170 Tflops of peak performance compute capacity and 3 PB of high-performance storage.  The Center’s extensive computing facilities, which are housed in a state-of-the-art 4000 sq ft machine room, include a generally accessible (to all UB researchers) Linux cluster with more than 8000 processor cores and QDR Infiniband, a subset (32) of which contain (64) NVidia Tesla M2050 “Fermi” graphics processing units (GPUs).   Industrial partners of the University have access to a cluster with more than 3400 processor cores and FDR Infiniband.  The Center maintains a 3PB IBM GPFS high-performance parallel file system.  The computer visualization laboratory features a tiled display wall, and a VisDuo passive stereo system.  
Dr. Thomas Furlani was appointed Director of the Center for Computational Research in 2006.  He served as Associate Director of CCR from 1998-2006.  Since 2010, Dr. Furlani has also served as the Interim Associate Vice President for Information Technology (CIO) of the University at Buffalo.
Strategic Strengths: CCR, which is a division of Computing and Information Technology (CIT), is a key player and significant contributor to UB 2020, the university's strategic plan, which has identified eight cross-disciplinary areas of strength indigenous to UB.  Each strength serves as an infrastructure for pulling together researchers from across the university to work cooperatively in pursuit of solutions to wide-ranging problems through a nontraditional collaborative approach.
In January of 1998, the Office of the Provost at the University at Buffalo, cognizant of the growing importance of computational science in science and engineering, formed an ad-hoc task group in "High Performance Research Computing". This group was comprised primarily of faculty members and staff with expertise in computational science. It was charged with evaluating the current status of computational science at the University, especially with respect to computing infrastructure. It was also charged with making specific recommendations of ways to improve the University's standing in the field of computational science.
CCR is housed on the ground floor of the University at Buffalo's Center of Excellence in Bioinformatics & Life Sciences building located in downtown Buffalo, NY.

The Buffalo-Niagara region is a major metropolitan area with a diverse blend of communities, each with its own distinct character and all united in a rich panorama of life.

For general questions about CCR, please fill out the form below.  For technical support questions, please visit the support section of our website.  Thank you!
The Center for Computational Research (CCR) at the University at Buffalo (UB) seeks to hire a computational scientist who wishes to  work in a dynamic research environment.  The position will involve a major role in life sciences based research. The successful candidate will work closely with researchers to help develop and deploy computational tools and scientific workflows to support research in the life sciences, including genomics based research. 

Minimum requirements:

A Master's degree in a scientific or engineering discipline, with preference in the life sciences, utilizing data intensive or compute intensive simulation and analysis. Combined education and experience equivalency will also be considered. Parallel computing expertise and experience in scientific software development.  Working knowledge of numerical methods in the sciences and engineering. The successful candidate will have an established record of publishing research results.  Excellent written and verbal communication skills are also required, along with the ability to work well in a team environment and publish research-driven results. Experience with the analysis and visualization of large datasets is highly desirable.