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AWARE-AI NRT
Welcome to the AWARE-AI NSF Research Traineeship (NRT) community at RIT!
Prospective and current RIT Ph.D. and MS students are welcome to review the benefits of a Traineeship position and how to apply to AWARE-AI by the March 1 application deadline, including for AWARE-AI’s one-year funded fellowships for eligible students in associated computing and information sciences, engineering, psychology, imaging science and mathematics programs. We especially encourage women, Deaf/Hard-of-Hearing and African American, Latino/a American, and Native American students to apply prior to their second year of graduate study.
AWARE-AI Trainees experience convergent AI research guided by accomplished faculty in research tracks and carefully curated and career-enhancing activities that directly address skill gaps in graduate AI curricula, and develop their network in a research community.
Select activities and resources are open to students at large such as mentor cafés, AI hackathons, and skills or competency building workshops. We look forward to seeing you at these events!
$34K
NRT Fellowships
Eligible applicants will be considered for one-year NRT fellowship positions/graduate research assistantships
4
Research Tracks
Trainees investigate convergent AI in software, hardware, human-computer interaction, or cognitive models tracks
200+
Students
The AWARE-AI NRT anticipates engaging 75 Trainees with/without fellowships and 125+ other students
Provost and Senior Vice President for Academic Affairs
AWARE-AI offers interdisciplinary and inclusive training in AI for graduate students from diverse backgrounds. The ethical and team-based AI research emphasized in the AWARE-AI program is crucial for shaping future human-AI innovations and human-centered AI systems.
Associate Provost and Dean, RIT Graduate School
AWARE-AI is a distinctive traineeship program, deeply committed to fostering diversity and inclusion within the field of AI while advancing graduate research at RIT. The Graduate School is privileged to be a partner in this progressive initiative.
This material is based upon work supported by the National Science Foundation under Award No. DGE-2125362. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.