Do you want to learn more about AI technologies, such as those behind tools like ChatGPT, DeepSeek, and CoPilot?
Would you like to work alongside researchers making breakthroughs in areas such as materials data science, animal ecology, biomedical imaging, and engineering?
Do you want to learn about using supercomputers to help solve tough scientific challenges?
The annual summer AI Research Experience (AIRE) program is seeking 10 postsecondary students in Ohio who are interested in working on an AI-focused research project with a university research team during summer 2026. The project provides a stipend for nine weeks of in-person or hybrid work at approximately 36 hours per week.
The aim of AIRE, managed by the OH-SCIPE project, is to increase awareness of the work of Cyberinfrastructure Professionals (CIP), individuals who provide IT support to university researchers, with a growing focus on supporting AI. The AIRE program can help undergraduates explore potential education and career paths in this emerging field.
As a program participant, you are matched up with a research team at Case Western Reserve University, The Ohio State University, or the University of Cincinnati to work on an AI research project for nine weeks, May through July. The OH-SCIPE team, including researchers and CIP, will provide training and guidance on the AI and HPC technologies needed for your project.
Testimonials:
“The internship gave me hands-on experience with real machine learning tools and workflows. If future applicants to the program are even slightly interested in AI, this is a great opportunity and fantastic way to learn and build something." - Filip Stopyra, Cuyahoga Community College, AIRE '25
“This internship helped push me to build a complete machine learning pipeline from scratch, combining real-world problem-solving with scientific rigor. If you're curious, driven, and ready to learn practical skills in AI, scientific thinking, and reproducible research, this is a rare opportunity to take ownership of a meaningful project.” - Isaac Wilson, Columbus State Community College, AIRE '25
"AIRE reinforced my passion for software development and cybersecurity, helped me refine my career goals, and expanded my professional network for future opportunities. I gained hands-on experience with real-world research, improved my problem-solving skills, and strengthened my ability to work in a team and communicate findings effectively." - Jesutomisin Oloyede, Sinclair College, AIRE '24
The 2026 program
The AIRE program will run for approximately nine weeks, from the week of May 18 through July 20. We are seeking 10 undergraduate science students (may have more than one with the same professor) from Ohio colleges to participate in AI research projects. Each participant will be assigned an AI research project and work with a science mentor to guide the research activities. Participants will also receive support from OH-SCIPE CIPs, who can provide guidance on using the software and computer systems needed for the projects. We anticipate having about five research experiences this year.
Schedule:
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Week 1 (May 18-22) – in-person kickoff event, followed by virtual training: Python, Linux, HPC basics
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Weeks 2-8 (May 26-July 10) – carry out project, meet regularly with science mentors, join CIP office hours
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Week 9 (July 13-17) – project wrap-up, deliverables to science mentor, prepare presentations
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July 20 – wrap-up and project presentations
Expectations:
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Available to work ~36/week during standard working hours on-site or hybrid as requested by the science mentor during the weeks listed above.
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Show initiative by learning about the computer software and systems required for the project.
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Participate in weekly meetings.
Eligibility/Requirements:
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You must be 18 years of age or older.
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You must be a domestic undergraduate student at a postsecondary institution in Ohio.
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You must be eligible to work in the U.S. without visa sponsorship.
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You must have completed one or more software programming courses or have equivalent programming experience.
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You must have a laptop or desktop computer to use for any remote work.
Process:
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Fill out the application form to be screened for eligibility by March 15, 2026.
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Eligible applications are anonymized and reviewed by research teams.
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Research teams identify and contact two to three applicants for interviews.
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You are informed if you are selected and are offered an AIRE position by April 13, 2026 (tentative).
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You accept and complete the EFT payment paperwork within 1 week of receiving the offer.
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Stipends totaling $5,000 will be distributed in five payments, contingent on participation, with the final payment authorized after program completion.
We are happy to answer your questions; please contact aire-info@osc.edu.
Background:
Faculty and research computing staff at Case Western Reserve University, Ohio Supercomputer Center, and University of Cincinnati were awarded funding from the National Science Foundation’s Strengthening the Cyberinfrastructure Professionals Ecosystem (SCIPE) program for the project “Interdisciplinary Research Support Community for Artificial Intelligence and Data Sciences,'' NSF Awards OAC-2320952, 2320953, 2320954.
We refer to this project as OH-SCIPE. The summer AIRE program is funded through this project to increase awareness of opportunities to use and support AI as a CI Professional. Please see this article or the project website for more information about OH-SCIPE.
Example Projects:
2025 program student project examples:
Jaser Hamad, Cuyahoga Community College, developed a method to determine which plastics are suitable for recycling and repurposing as new products. The current method for evaluating plastics is time-consuming and labor-intensive. Hamad, working with faculty member Sanmukh Kuppannagari of Case Western Reserve University, built a machine learning system that reads a plastic's “fingerprint” to determine its level of deterioration from environmental factors. AI returns an accurate, immediate assessment that can be fully reproduced by researchers or quality assurance teams at plastics recycling companies.
Isaac Wilson, Columbus State Community College, worked with researchers at Ohio State’s Imageomics Institute, which focuses on extracting biological traits from images of living organisms. Wilson used AI models to scan images of water lilies, mushrooms, red foxes, and blue jays to identify patterns in their traits. The student created an algorithm for sorting photos, compared sets of species, and refined software documentation. This information can help scientists identify and examine biological attributes in individual organisms and species. Wilson, working with Ohio State’s Matt Thompson, Elizabeth Campolongo, and Sam Stevens, learned to write Python scripts and use OSC’s Ascend HPC cluster to process data.
Oleksandr Vykliuk, Cuyahoga Community College, used machine learning tools to develop a better method of reviewing logs to identify the source of failures in HPC systems. Failures can be costly, representing $100,000 per hour in system downtime and lost research productivity. While system logs capture anomalies in HPC performance, they often contain a large amount of data that can be difficult for administrators to parse. Working with Weicong Chen of Case Western Reserve University, Vykliuk created a method to automatically detect the problem by reviewing hardware events, job status logs, node health, and network traffic.
Filip Stopyra, Cuyahoga Community College, used machine learning models to build a process that can detect real and fake scientific images. Working with Weicong Chen of Case Western Reserve University, Stopyra used powerful models to extract features from images and evaluate their accuracy, fine-tuning the process to achieve the highest accuracy. Stopyra learned how to use Jupyter Notebooks for the project and gained more experience with Python.
Oluwatomisin Fayomi, Franklin University, created an AI interface for a scientific lab web portal that could answer visitor questions. The project required Fayomi to develop a communication protocol between the website's back end and front end. Fayomi, who worked with Rajiv Ramnath of Ohio State on the project, studied various AI models, learned to deploy one using Python, acquired new coding skills, and gained experience collaborating with a large GitHub group.
