NSF award 2537092 · Howard University

Research Coordination Network on Assessing and Predicting Jobs Outcomes in AI (RCN APJO-AI)

Final report due

28 January 2028

in 467 days · The award ends on 30 September 2027.

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Decide about an extension2 Jun 2027in 227 days
award ending 2027-09-30 · Research.gov
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Extension request16 Aug 2027in 302 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Sep 2027in 337 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Jan 2028in 467 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Jan 2028in 467 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Jan 2028in 467 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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NSF lists this award's end date as 30 September 2027.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 January 2028.

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Award card

Award number: 2537092
Period of support: 1 Oct 2025 – 30 Sep 2027
Amount: $499,983
Awardee: Howard University, Washington, DC
Program: TIP-CHIPS KTA-1 AI-ML
Directorate: TIP

Abstract

The Assessing and Predicting Job Outcomes in AI (APJO-AI) research coordination network (RCN) will establish a national network across sectors, disciplines, and organizations focused on assessment of the current state of AI jobs and to predict future trends, in order to contribute towards a strong national economy given that AI is reshaping nearly every sector of society. There is a pressing national need to build a…

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