From Cold Email to Computational Neuroscience at Harvard: All About Urmeshree Magesh’s Co-op at Harvard
- Widler Casy
- 1 day ago
- 4 min read
Biotech Intern Newsletter: Spotlight on Urmeshree Magesh
Welcome to this edition of the Biotech Intern Newsletter. Today, we are excited to spotlight Urmeshree Magesh, whose on-site internship at Brigham and Women’s Hospital and Harvard Medical School highlights the impact interns can make at the intersection of computational biology and neuroscience, and how initiative, mentorship, and thoughtful problem-solving drive meaningful research outcomes.
Internship Snapshot
Company: Brigham and Women’s Hospital and Harvard Medical School, Butovsky Laboratory
Location: On-site, Boston, Massachusetts
How It Started: “I found this internship by cold emailing the principal investigator after reading about their lab’s work.”
After introducing herself, sharing her resume, and explaining her research interests, Urmeshree received positive feedback on her background. This initial outreach led to further conversations and ultimately an internship offer.
At the Butovsky Laboratory, Urmeshree worked on computational neuroscience projects focused on Alzheimer’s disease.
A Day in the Life
Urmeshree describes her internship in one sentence as: “I developed and automated single-cell and single-nucleus RNA sequencing data analysis pipelines to study microglia and astrocyte interactions in Alzheimer’s disease.”
Her work centered on transforming large-scale multi-omic datasets into interpretable biological insights that could support ongoing neuroscience research.
Lessons from the Experience
Biggest Learning: “I learned how to translate raw multi-omic data into biologically meaningful insights, bridging computational analysis with real-world neuroscience research.”
This experience reinforced the importance of connecting technical outputs to biological context and research goals.
Best Advice Received
One of the most impactful lessons Urmeshree received during her internship was: “Always validate your findings biologically, not just statistically.”
This advice shaped how she approached analysis, pushing her to look beyond numerical significance and focus on biological relevance.
Wish I Had Known
“I wish I had understood how crucial good documentation and version control are when collaborating across a large, multidisciplinary research team.”
Working in a collaborative environment made it clear that clear documentation is essential for efficiency, reproducibility, and teamwork.
Wish I Had Learned Earlier
“I wish I had more exposure to large-scale data management on cloud or high-performance computing systems for scaling single-cell workflows.”
Earlier familiarity with these systems could have helped her scale analyses more efficiently.
Fun Moments and Connection
Most Fun Experience: “Presenting my Shiny data exploration app to the lab.”
Seeing researchers interact with live transcriptomic data in real time was a rewarding moment that highlighted the practical impact of her work.
Biggest Struggle and the Lesson
Early in the internship, Urmeshree struggled with integrating multiple datasets that had inconsistent annotations.
“I learned to build robust preprocessing scripts and always standardize metadata early in the workflow.”
In another challenge, her R pipeline repeatedly crashed while integrating APOE genotype stratified data. Instead of applying temporary fixes, she redesigned the workflow step by step, modularized the scripts, and added error handling. This solution later became the foundation for the lab’s standardized analysis toolkit.
Behind the Scenes
Resources That Could Have Helped More: “I wish I had used our institution’s research computing and training resources more, especially workshops on R, cluster usage, and reproducible workflows.”
These resources offered hands-on guidance on optimizing code, working efficiently on computing clusters, and structuring projects for scalability.
Who Made It Possible: “I credit my mentor, Madison Carpenter, for constantly pushing me to connect computational results with biological interpretation and for guiding me through each project milestone.”
Advice for Future Interns
Words of Wisdom: “Treat every small task like a deliverable. It builds trust, demonstrates accountability, and opens doors to bigger opportunities.”
What Interns Should Focus On: “Focus on learning how your work fits into the bigger research or organizational goal. Technical skills matter, but understanding the why behind your work matters more.”
Additional advice includes asking why as often as how, sharing work early even if it is not perfect, documenting everything, being honest when stuck, and treating internships as long-term professional relationships rather than short-term roles.
A Defining Story
Early in the internship, Urmeshree’s R pipeline repeatedly crashed while integrating APOE genotype stratified data.
“Instead of patching it manually, I redesigned the workflow step by step, modularized the scripts, and added error handling.”
What began as a technical obstacle became a lasting contribution, forming the basis for the lab’s new standardized analysis toolkit.
Rapid Fire
Coffee or Tea: Coffee
Meetings: In-person
Mountains or Beaches: Mountains
Closing Thoughts
Urmeshree Magesh’s internship at Brigham and Women’s Hospital and Harvard Medical School demonstrates how initiative, strong mentorship, and thoughtful problem-solving can lead to meaningful scientific contributions. Her story is a reminder that impactful internships are built not only on technical skills, but also on curiosity, communication, and a commitment to understanding the broader purpose behind the work.
Connect with Urmeshree Magesh, on LinkedIn to follow her journey in biotech.
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