Fall 2025 Internships – Applications Now Open
The Institute of Applied Artificial Intelligence and Robotics (IAAIR) is dedicated to advancing AI research and real-world applications across industries. Our mission is to bridge the gap between theoretical research and practical deployment by creating innovative, scalable, and impactful AI solutions. We collaborate with industry leaders, researchers, and technology experts to address complex challenges in AI, robotics, automation, and data science.
If you are passionate about solving real-world challenges using Applied AI and eager to gain hands-on research experience, the IAAIR Applied Research Internship offers a unique opportunity to work on cutting-edge projects, develop practical applications, and collaborate with leading AI researchers and industry experts.
Internship Intake
Applications for the Fall 2025 cohort are currently open. The internship runs from 22 September – 12 December 2025 (12 weeks, full-time).
Due to the high volume of applications, only shortlisted candidates will be contacted.
Project Tracks
Interns will contribute to one of five projects, falling into two distinct tracks:
Qualitative Research Projects
Qualitative research focuses on understanding human, cultural, and organizational perspectives through interviews, surveys, thematic analysis, and case studies rather than coding or algorithm development. These projects emphasize insight generation, frameworks, and research synthesis.
GroundTruth Commons: Community Observation Protocols for AI Disaster Maps (Qualitative)
Develop participatory frameworks and community-driven data protocols to strengthen trust in AI-generated disaster response tools.OpenAg Global Perspectives: Comparing AI in Agriculture Across Regions (Qualitative)
Compare agricultural AI adoption across developed and developing regions, exploring accessibility, affordability, and contextual challenges.Building Pathways to Agricultural AGI: An OpenAg Research Internship Study (Qualitative)
Scope and evaluate components for long-term agricultural AI systems, including specialized models, knowledge frameworks, and governance approaches.
Technical / Applied AI Projects
These projects require strong coding, mathematical, and technical skills, focusing on developing, testing, and deploying AI models.
Automated Emerald Color Grading with Hybrid Color Spaces and Probabilistic Modelling (Technical/Applied AI)
Build AI-based grading pipelines for gemstones using calibrated imaging, hybrid color features, and probabilistic modelling.Impact Measurement with AI: Integrating Quantitative Indicators and Qualitative Evidence (Technical/Applied AI)
Design, implement, and evaluate an AI system that measures, verifies, and explains program impact by combining quantitative indicators with qualitative evidence.
Factoring Emotional Intelligence in Audio-based Conversational AI (Technical/Applied AI)
Design affect-aware conversational AI models that capture empathy and emotional nuance through speech and acoustic analysis.
Eligibility Criteria
Because the internship spans two distinct tracks, the eligibility differs slightly:
For Qualitative Research Projects
Applicants should:
Be enrolled in, or have recently completed, a degree in: Social Sciences, Science & Technology Studies, Anthropology, Sociology, Development Studies, Public Policy, or related fields.
Have strong skills in qualitative research methods (e.g., interviews, surveys, focus groups, thematic coding).
Demonstrate ability to synthesize insights into structured frameworks and reports.
Possess excellent written communication skills for academic and policy audiences.
Have a strong interest in Artificial Intelligence and a willingness to learn about AI technologies and their societal impact.
Interest in domains such as agriculture, disaster response, or technology adoption is highly desirable.
For Technical / Applied AI Projects
Applicants should:
Be pursuing a degree in: Artificial Intelligence, Machine Learning, Computer Science, Data Science, Robotics & Mechatronics, Mathematics & Statistics, or Electrical & Electronic Engineering.
Hold a minimum GPA of 3.5 on a 4.0 scale (or equivalent).
Have proficiency in Python and libraries such as NumPy, SciPy, and Matplotlib.
Possess foundational knowledge of machine learning or quantum computing (depending on project).
Prior exposure to research projects, open-source contributions, or publications is desirable.
Important Notes:
This internship is not affiliated with any university. However, if selected, IAAIR can provide the necessary documentation required by your university to facilitate credit recognition (if applicable) or internship approval. It is the applicant’s responsibility to communicate with their university and ensure that the internship aligns with their academic or professional requirements.
IAAIR does not provide visa sponsorships or visa-related letters. Applicants must have the legal right to work or intern in their respective locations and are solely responsible for ensuring compliance with all visa, immigration, and work authorization requirements.
Internship Details
Duration: 12 weeks
Commitment: Full-time
Internship Type: Unpaid, undertaken for educational and professional experience
Mode: Remote and on-site options available (On-site internships will be at IAAIR headquarters in Memphis, Tennessee, USA)
Intern Responsibilities
All interns, regardless of track, will:
Conduct background research and summarize findings.
Participate in weekly progress meetings with supervisors.
Deliver a mid-term presentation (Week 6).
Deliver a final presentation and demo/report (Week 12).
Submit a final research report documenting methodologies, results, and insights.
Track-specific responsibilities:
Qualitative: designing interview protocols, analyzing survey/interview data, writing case studies, producing comparative insights.
Technical: developing models, running experiments, implementing prototypes, documenting code.
Internship Completion & Certificate
Interns who successfully complete the program will receive an Internship Completion Certificate. The certificate will be issued only after:
The final presentation has been delivered at the end of the internship.
The final report has been submitted and reviewed by IAAIR.
Failure to complete these requirements will result in no certificate being issued.
Benefits of the Internship
This internship provides applied research experience and will:
Gain hands-on research experience in applied AI (both technical and societal dimensions).
Build expertise in either AI model development or qualitative analysis of AI adoption.
Strengthen research communication, writing, and presentation skills.
Contribute to projects with potential for academic publication or industry adoption.
Network with researchers, industry professionals, and global collaborators.
Application Process
Apply online (select Qualitative or Technical track). The applications must be submitted here.
Shortlisted candidates will be invited for an interview.
Technical candidates may have an additional coding/research round.
Final stage includes reference checks (two required).
Should there be any further questions, please get in touch at internships@iaair.ai