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EPSCoR Research Infrastructure Improvement Program: Track-2 Focused EPSCoR Collaborations (RII Track-2 FEC)

October 24, 2019

For more information see the NSF website: https://www.nsf.gov/pubs/2020/nsf20504/nsf20504.htm?WT.mc_id=USNSF_25&WT.mc_ev=click

The following EPSCoR jurisdictions are RII-eligible for the FY 2020 RII Track-2 FEC competition: Arkansas, Iowa, Kansas, Nebraska,  North Dakota, Oklahoma, and South Dakota.

  • There is a limit of a single proposal from each submitting organization.  
  • Each proposal must have at least one collaborator from an academic institution or organization in a different RII-eligible EPSCoR jurisdiction as a co-Principal Investigator (co-PI) and must promote collaborations among researchers in EPSCoR jurisdictions.

Letter of Intent Due Date: December 20, 2019

Full Proposal Deadline:  January 24, 2020

 

Call to Participate in Data Mobility Exhibition

September 12, 2019
Greetings Current and Prior Campus Cyberinfrastructure (CC*) Awardees & R&E Community Members;
 
Data mobility is a critical component of the process of science.  Being able to predictably and efficiently move scientific data between experimental source, processing facilities, long-term storage, and collaborators is a common use case that transcends the boundaries of research disciplines.  
 
Current and previous CC* awardees, along with the greater R&E community, are encouraged to participate in an exciting and beneficial data mobility exhibition that will be conducted community wide, and highlighted at the 2019 and 2020 CC and CICI PI Meetings.  Using reference data sets, and existing or planned campus CI components, participants will download, measure, and potentially improve their scientific data movement capabilities.  
 
Steps to participate:
 
1) Create a brief (1-2 page) description of the network and data architecture for your campus environment using this template:
 
 
An example can be found here:
 
 
2) Prepare an environment to transfer reference data sets.  This should be done by utilizing a “local” data transfer machine, and the Globus Connect software.  It is recommended to use a machine that is already functioning for scientific use vs. a purpose built resource (e.g. let this be as close to production as you can).  Help can be requested at epoc@iu.edu 
 
3) Download the reference data sets and record the results.  Information on this is available here:
 
 
4) Share the description, and your results on a standardized spreadsheet:
 
 
With the organizers via this form:
 
 
5) For those that want to accelerate their results, 1:1 assistance, via the Engagement and Performance Operations Center (EPOC), is available: epoc@iu.edu 
 
This event begins “now”, and will extend for a full year, through the CC* 2020 PI meeting.  Participation is open to all – no requirement to be involved with CC* or CICI, in fact we would encourage sharing of this with other interested parties that may not see the initial message.  The purpose of this activity is to characterize the performance expectations for data movement at the researcher level, and improve these as needed across the R&E community.  Its a big task, and there may be challenges, but this community can and will meet them.  
 
More information on this event can be found here:
 
 
A webinar was held Friday August 30th @ 2pm ET to discuss the motivations and structure of this event further, it is available for viewing on YouTube
 
 
We encourage all interested parties to consider this event, questions or comments can be sent to epoc@iu.edu or discussion can continue on the CI Engineering mailing list: cybinf-engr@es.net 
 

South Dakota State U Seeks Research High Performance Computer Specialist (HPC Facilitator)

August 28, 2019

https://yourfuture.sdbor.edu/postings/17061

South Dakota State University is located in Brookings, SD.

The Division of Technology & Security (DTS) at South Dakota State University (SDSU) is announcing an opening for a 12-month, full-time, benefit-eligible Research High-Performance Computing (HPC) Specialist. This position will support computational applications and develop program algorithms that provide solutions to solve scientific problems associated with SDSU research projects. Must be authorized to work in the U.S. Sponsorship is not available for this position.

SDSU is especially interested in candidates that can contribute to and/or coordinate course offerings that address the experiences of underrepresented minorities in organizations. Women, minorities, veterans, and people with disabilities are especially encouraged to apply.

RESPONSIBILITIES:
The successful candidate will engage the university research community with efforts that include the design, planning, coordination, implementation, and training of HPC application, programming, and other associated HPC solutions to support the computational needs within SDSU grant research.

MINIMUM QUALIFICATIONS:
• Ph.D. completed by the date of hire;
• One year of HPC application experience within-cluster and single server environment(s), supporting CPU and data-intensive research;
• Experience engaging researchers (and graduate staff) to understand their research and propose the appropriate computational methodology to solve their scientific problems; 
• Experience leading training workshops/similar and developing HPC instructional materials or actively contributing as Service Personnel, PI, or a Co-PI on research grant proposals; 
• Demonstrated ability to work as a contributing team member; 
• Excellent oral and written communication skills;
• Strong interpersonal skills;
• Demonstrated use of technology in managing and/or delivering research applications and associated computer programs;
• Valid driver’s license, or ability to obtain one within 30 days of hire.

PREFERRED QUALIFICATIONS:
• At least three years of computational experience developing HPC application solutions;
• Ph.D. in a Computer or Data Science field;
• At least three years of computational experience in higher education working within a research computing department.
• Involvement in the development of instructional training materials for HPC and has actively contributed as Service Personnel, PI, or a Co-PI on research grant proposals.