CAST10 Archives

April 2012


Options: Use Monospaced Font
Show Text Part by Default
Show All Mail Headers

Message: [<< First] [< Prev] [Next >] [Last >>]
Topic: [<< First] [< Prev] [Next >] [Last >>]
Author: [<< First] [< Prev] [Next >] [Last >>]

Print Reply
"Luke Achenie @ NSF/CBET/PRE" <[log in to unmask]>
Reply To:
Luke Achenie @ NSF/CBET/PRE
Fri, 6 Apr 2012 09:40:48 -0400
text/plain (39 lines)

Announcement 12-549


Full Proposal Window: June 3, 2012 - July 3, 2012


Computational and Data-Enabled Science and Engineering (CDS&E) is a NSF-wide
cross-disciplinary activity that coordinates relevant disciplinary and
interdisciplinary programs at the intersection of mathematics and
statistics, computer and computational science, and the core science and
engineering disciplines. It is dedicated to the development and use of
advanced computational methods, information processing, data mining and
analysis, and advanced cyberinfrastructure to enable and execute
transformative scientific discovery and engineering innovation, and to the
education of experts and non-experts in computation, including workforce
development and training.

The CDS&E in engineering (CDS&E-ENG) program recognizes the importance of
engineering in CDS&E and vice-versa. Many natural and built engineering
processes, devices and/or systems require high fidelity simulations over
disparate scales that can be interrogated, analysed, modeled, optimized or
controlled, and even integrated with experiments or physical facilities.
This program accepts proposals that confront and embrace the host of
research challenges presented to the science and engineering communities by
the ever-expanding role of computational modeling and simulation on the one
hand, and experimental and/or observational data on the other. The goal of
the program is to promote the creation, development, and utilization of the
next generation of theories, algorithms, methods, tools, and
cyberinfrastructure in science and engineering applications.

The CDS&E-ENG program will support fundamental research that will address
the aforementioned computational and data-related challenges in science and
engineering. Proposals are expected to be relevant to engineering and to
have cross-cutting and integrative themes.