
A novel base editing technology invented at Rutgers, with the potential to be used for the creation of new cell and gene therapies, will be made available to researchers worldwide through an exclusive partnership with the Horizon Discovery Group.
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DUNS Number: 001912864
Institutional Profile (IPF) Number for NIH: 1196203
NSF Awardee Organizational Codes: 00262940000
Cage Code: 4B883
Congressional District: NJ-006
Carnegie Classification Code: Research I
FICE Code: 006964
Tax ID or 10-Digit EIN: 1226001086A1
DUNS Number: 625216556
Institutional Profile (IPF) Number for NIH: 1196202
NSF Awardee Organizational Codes: 0047415000
Cage Code: 4EF09
Congressional District: NJ-001
Carnegie Classification Code: Master's I
FICE Code: 004741
Tax ID or 10-Digit EIN: 1226001086A1
DUNS Number: 130029205
Institutional Profile (IPF) Number for NIH: 1196204
NSF Awardee Organizational Codes: 00262940000
Cage Code: 4CPZ9
Congressional District: NJ-010
Carnegie Classification Code: Doctorall II
FICE Code: 002631
Tax ID or 10-Digit EIN: 1226001086A1
DUNS Number: Varies by school
Institutional Profile (IPF) Number for NIH: Varies by school
NSF Awardee Organizational Codes: Varies by school
Cage Code: 4CPZ9
Congressional District: NJ-010
Carnegie Classification Code: Doctorall II
FICE Code: 002631
Tax ID or 10-Digit EIN: 1-462354111
Rutgers researchers are making a meaningful difference in the world. See the latest announcement of faculty grants and awards.
A novel base editing technology invented at Rutgers, with the potential to be used for the creation of new cell and gene therapies, will be made available to researchers worldwide through an exclusive partnership with the Horizon Discovery Group.
A new group of socially-cognizant roboticists will emerge from Rutgers thanks to a $3M National Science Foundation Research Traineeship (NRT) grant. The first major traineeship grant awarded to the School of Engineering will equip researchers and graduate students with insightful research that integrates technology domains of robotics, computer vision and machine learning with social and behavioral sciences.
This novel technology would replace the traditional fiber-based filter by an arrangement of liquid droplets that capture and remove the particles from air, eliminating waste and reducing maintenance.