A $400,000 National Science Foundation grant will bring artificial intelligence and machine learning into biology courses and faculty-mentored research at Alabama State University, according to the university's announcement. The three-year project begins in September 2026 and is led by Dr. Manoj K. Mishra, a biology professor and founding director of the ASU Cancer Research Center. Its headline number for students is simple: 15 undergraduate spots.
For readers deciding whether this matters to them, the practical question is not what the grant symbolizes. It is what a student at ASU — or at a comparable Historically Black College and University watching this model — can actually do with it. The answer, based on the university's own description of the project, comes down to three moves: get into the funded cohort, learn to analyze biological data with computational tools, and use faculty-mentored research to build toward graduate study or a biomedical career. This connects to our earlier piece, Rubin Observatory's First Data Drop Delivered 11,000 New Asteroids.
What does the grant actually fund?
The project, titled "TIP: Infusing Artificial Intelligence and Machine Learning into Biology Education and Research at Alabama State University," runs for three years and does two things. First, it changes what happens in biology courses, adding AI and machine learning content to the curriculum. Second, it funds faculty-mentored research, where undergraduates work on real scientific questions under a professor's direction.
The 15 funded undergraduates are the concrete entry point. According to the announcement, they will learn to analyze biological data and use computational tools to investigate scientific questions. The stated goal is to build skills for graduate study and for careers in fields such as computational biology and biomedical data science.
Readers who want to understand how a grant like this moves from application to award can follow the process in How an NSF Grant Actually Gets Made, Step by Step. The mechanics matter, because a three-year award shapes what a department can promise and for how long.
How can a student act on it?
The university's announcement does not describe an application process, a deadline, or eligibility criteria for the 15 spots. That gap is material: a student who wants one of those positions needs to ask the biology department directly. What the announcement does support is a checklist of what the funded experience involves.
- Hands-on work: the 15 undergraduates learn by analyzing biological data, not by watching demonstrations.
- Computational tools: the training covers AI and machine learning methods applied to biological questions.
- Faculty mentorship: the research component runs under faculty supervision, led by Mishra's team.
- A stated pathway: the skills are aimed at graduate education and careers in the biomedical workforce.
Each of those four points comes straight from the university's description. A student evaluating whether to pursue a spot can weigh each one against their own goals — and can ask the department which courses will carry the new AI and machine learning content, since the grant funds curriculum change as well as research.
Why is ASU framing this as a national-need project?
Mishra's stated argument is that AI is reshaping biology across the board. "Artificial intelligence is revolutionizing nearly every aspect of modern biology, from disease diagnosis and drug discovery to genomics and precision medicine," he said in the announcement. He also noted that the grant addresses a growing national need to equip students at Historically Black Colleges and Universities with AI and data science skills.
That framing has a practical consequence for students elsewhere. If the project works as described, it produces a repeatable model. "By integrating AI and machine learning into biology education and research, we are creating a sustainable model that broadens participation in STEM, strengthens workforce readiness, and prepares the next generation of scientific innovators," Mishra said. Students at other HBCUs can watch whether that model holds — and ask their own institutions whether something similar is possible.
What should readers watch for as the project runs?
The announcement is the university's own account of its award, and it is the only source supplied here. It describes intentions and structure, not outcomes. Three things would show whether the project delivers on them.
- Whether the 15 undergraduate spots fill and what those students produce — theses, conference presentations, or graduate-school placements.
- Which specific courses change, and how quickly the AI and machine learning content reaches students outside the funded cohort.
- Whether the "sustainable model" Mishra describes outlasts the three years of funding.
The project builds on ASU's existing work in cancer biology, immunology, and biomedical research, according to Mishra. The Cancer Research Center at ASU, which he founded and directs, describes itself as focused on cancer biology, tumor immunology, health disparities, and precision medicine, with training for undergraduate and graduate students. That gives the new AI curriculum an existing research base to attach to.
For readers tracking how universities spend research money and what it buys students, the wider picture of academia — its funding, careers, and publishing politics — is where a story like this sits. The narrow answer, though, stays local: 15 spots, three years, and a curriculum that will soon teach biology students to work with data the way the field now does.
