Q: How can I get involved with the AIRE Lab?
A: You can explore opportunities to collaborate, study our findings, or contribute to our mission by reaching out to us through the Contact Us form.
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Q: Does the AIRE Lab offer training programs?
A: Yes, we provide training services to equip individuals and organizations with knowledge, skills, and tools related to AI, evaluation, and equity.
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Q: What are some of the current projects at the AIRE Lab?
A: Our current projects include research on AI in education, climate change and childhood development, and sustainable livelihoods for refugee fathers. https://airelab.online/projects/
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Q: Are there opportunities for graduate students to get involved in research projects at the AIRE Lab?
A: Yes, the AIRE Lab often collaborates with graduate students on research projects related to AI, evaluation, and social impact.
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Q: Does the AIRE Lab offer assistantships or funding for graduate students?
A: Graduate research assistantship positions may be available, depending on current project needs and funding. Inquire for the latest opportunities.
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Q: Can graduate students use the AIRE Lab’s resources and expertise for their thesis or dissertation research?
A: The AIRE Lab welcomes opportunities to support graduate students’ research efforts and professional development aligned with our mission and expertise areas. The lead researchers on the team are available to offer comprehensive workshops on various topics such as impact evaluation, advanced econometrics, psychometrics, machine learning, etc. This can also be linked to the service page where we can list the workshops we offer. https://airelab.online/services/
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Q: Are there internship openings available for graduate students at the AIRE Lab?
A: Internship opportunities may be offered periodically. Check our website or inquire directly using our contact information (airelab@ukt.edu; airelab.online@gmail.com) about upcoming openings.
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Q: What coursework or skills are recommended for students interested in the AIRE Lab’s work?
A: Relevant coursework includes AI, machine learning, statistics, evaluation methods, and critical qualitative and quantitative methods, mixed methods.