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The following programs have due dates that fall between October 1 - 25, 2013, and these dates are being revised due to the Federal  government shutdown. These revised dates apply whether the proposal is being submitted via the NSF FastLane System or  Grants.gov. Due to compressed proposal deadlines resulting from the shutdown, proposers are advised that they may experience a  delay when contacting IT Help Central with technical support questions. Frequently asked questions regarding these date changes  are available on the Resumption of Operations page on the NSF website at: http://www.nsf.gov/bfa/dias/policy/postshutdown.jsp. 

This Funding Opportunity Announcement (FOA) invites applications from the Program Directors/Principal Investigators of the current Building Infrastructure Leading to Diversity (BUILD) awards. BUILD is part of the Enhancing the Diversity of the NIH-Funded Workforce Program, also known as the Diversity Program Consortium (DPC), consists of three integrated initiatives: BUILD, the National Research Mentoring Network (NRMN) and the Coordination and Evaluation Center (CEC). The purpose of the funding is to allow BUILD sites to continue to implement and evaluate the multi-pronged student, faculty, and institutional interventions to enhance diversity in the NIH biomedical research workforce. In preparation for the second phase of the BUILD initiative, the applicants are expected to provide plans to transition into sustainable models for enhancing diversity in the biomedical research fields at their institutions. Applicants are also expected to develop an effective training, mentoring, or research capacity building intervention that will be disseminated to other institutions to increase the national impact of the initiative.

The Energy, Power, Control, and Networks (EPCN) Program supports innovative research in modeling, optimization, learning, adaptation, and control of networked multi-agent systems, higher-level decision making, and dynamic resource allocation, as well as risk management in the presence of uncertainty, sub-system failures, and stochastic disturbances. EPCN also invests in novel machine learning algorithms and analysis, adaptive dynamic programming, brain-like networked architectures performing real-time learning, and neuromorphic engineering. EPCN's goal is to encourage research on emerging technologies and applications including energy, transportation, robotics, and biomedical devices & systems. EPCN also emphasizes electric power systems, including generation, transmission, storage, and integration of renewable energy sources into the grid; power electronics and drives; battery management systems; hybrid and electric vehicles; and understanding of the interplay of power systems with associated regulatory & economic structures and with consumer behavior.