Summary
The NSF Research Traineeship (NRT) program seeks proposals that explore ways for graduate students in research-based master’s and doctoral degree programs to develop the skills, knowledge, and competencies needed to pursue a range of STEM careers. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas, through a comprehensive traineeship model that is innovative, evidence-based, and aligned with changing workforce and research needs. Proposals are requested that address any interdisciplinary or convergent research theme of national priority, as described in section II.D below. The NRT program addresses workforce development, emphasizing broad participation, and institutional capacity building needs in graduate education. The program encourages proposals that involve strategic collaborations with the private sector, non-governmental organizations (NGOs), government agencies, national laboratories, field stations, teaching and learning centers, informal science centers, and academic partners. NRT especially welcomes proposals that reflect collaborations between NRT proposals and existing NSF Eddie Bernice Johnson Inclusion across the Nation of Communities of Learners of Underrepresented Discoverers in Engineering and Science (INCLUDES) Initiative , Research Experiences for Undergraduates (REU) , Louis Stokes Alliances for Minority Participation (LSAMP) , NSF Scholarships in Science, Technology, Engineering, and Mathematics (S-STEM) , and NSF STEM Ed Organizational Postdoctoral Fellowship program (STEM Ed OPRF) projects, provided the collaboration will strengthen both projects. Researchers at minority serving institutions and emerging research institutions are strongly encouraged to submit proposals. Collaborations between NRT proposals and existing NSF INCLUDES projects should strengthen both NRT and INCLUDES projects.
Eligibility
- Other
Funding categories
- Science Technology and Other Research and Development
Official source and attribution
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