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News and Announcements
Creative Scholarship with Music-Making in Prison Contexts
Wednesday, November 11, 2026
Opportunity to work with Music Education Professor on music-making in prison contexts. Responsibilities will vary based on student interests and schedule but may include, collaborating on original music with an incarcerated songwriter, creating music videos for original songs collaborating with various artists, build social media campaigns and more.
ALT Lab Research Competition
Tuesday, November 10, 2026
The ALT Lab and DeLTA Center are offering funding, equipment access, and methods support for trainee-led learning research in 2027.
Cech Fellows Program
Friday, November 6, 2026
The Cech Fellows Program is a paid, nine-week summer research experience for rising college juniors and seniors, offering hands-on research with leading HHMI scientists, professional mentorship, and opportunities to explore careers in biological and biomedical research.
AGA Awards
Friday, November 6, 2026
The AGA offers two mentored research programs for undergraduates from groups traditionally underrepresented in biomedical research: a 10-week summer program and a 10-month academic-year program focused on digestive diseases. Both provide stipends and opportunities for professional development, with the academic-year program also including AGA membership and travel support to Digestive Disease Week®.
Issuree Lab
Tuesday, November 3, 2026
This position offers a motivated individual a continuous, immersive research experience, whether to build a lasting connection to science or to assess whether it’s the right path for them.
Beginning and Early Stage Translational (BEST) Research Summer Training Program
Monday, November 2, 2026
The BEST program is for 10 weeks, on campus. Students will be paid for working 40 hours/week along with a housing stipend of up to $1000
Reliable AI for geospatial data: when can we trust AI maps?
Tuesday, October 27, 2026
Project and Position Details
AI models are increasingly used to map floods, land cover, and urban change from satellite imagery and other geospatial data. But these models can be confidently wrong, and their errors are often concentrated in particular places, such as rural or data-scarce regions, where decisions may matter most. This project develops methods to measure, explain, and correct where and why geospatial AI fails, so that its outputs can be used responsibly.