West Virginia Press Association
WASHINGTON, DC – U.S. Senator Joe Manchin (D-WV), member of the Senate Appropriations Committee, announced $1,759,760 from the National Science Foundation (NSF) for four research projects at West Virginia University (WVU). +The funding will support research into sustainability, electronic fields, livestock management, and the Supreme Court’s decision-making process.
“West Virginia University continues to make our state proud with innovative research projects. I’m pleased the National Science Foundation is investing more than $1.7 million in these four important initiatives, which will advance our understanding of agriculture, physics, and Supreme Court decisions,” said Senator Manchin. “As a member of the Senate Appropriations Committee, I will continue advocating for resources that support our universities and bolster academic research across West Virginia.”
Individual awards listed below:
- $1,076,144– West Virginia University: CAREER: Securing the Future of Electric Field Measurements in Space Physics
- This project will optimize electric field instrumentation to advance space physics knowledge.
- $548,943 – West Virginia University: CAREER: Leveraging Data Science & Policy to Promote Sustainable Development Via Resource Recovery
- This program will develop, apply, and assess a data-driven framework that integrates data science, life cycle modeling, and policy analysis to promote sustainable, context-sensitive resource recovery in rural agricultural regions.
- $84,673 – West Virginia University: Collaborative Research: Precedent-Altering Opinions and Collegiality on the Supreme Court
- This project will investigate the role judicial collegiality plays in the Supreme Court decision-making process, with a particular focus on how relationships shift when the Court alters past decisions and overturns acts of Congress.
- $50,000 – West Virginia University: I-Corps: Predictive algorithms to determine individual feed intake in beef cattle
- This project is based on the development of a predictive algorithm to make use of daily animal weight and water intake, along with weather data, to predict daily feed intake.
