This blog/article is all about the experience of Mr. Rohit Agarwal, who completed his B.tech with integrated M.tech from IIT Dhanbad (Batch — 2015–2020), who pleasurably shared the experience of his research internship at NIBMG (National Institute of Biomedical Genomics, Kalyani), West Bengal with RECOOLS, which other students might find relatable and use his experience as their advantage with their whole research internship process.
A research internship is usually undertaken in the final or pre-final year of graduation or post-graduation. At the core of most research internships is a research project of your own. While working on it, you learn new scientific techniques, design experiments, analyze results, and formulate different hypotheses.
You work closely with a supervisor or a professor who guides you. As an intern, you attend lab meetings, symposiums, and classroom lectures. You will work closely with scientists and will get an opportunity to demonstrate your own scientific insight. Most science and research organizations offer internships as a form of work experience or partial fulfillment of the degree.
Getting acquainted with internships
I was enrolled in the 5-year B.tech with integrated M.tech in Mathematics and Computing at Indian Institute of Technology (Indian School of Mines) Dhanbad and heard about a research internship in junior year when my batchmates applied for Mitacs.
Application Process Being reluctant to the process of cold mailing random professors, a common practice followed by many students, I came to know about Mitacs and did my internship at NIBMG National Institute of Biomedical Genomics, Kalyani, West Bengal. It was a data science-based internship on genomic data.
Points to be considered while preparing an application:
- It consists of 1–3 letters of recommendation.
- Try to approach professors having rich research experience in your field of work.
- Make sure to interact with professors as they’ll give LORs easily then.
- If the professor is not acquainted with you, write a sample LOR consisting of interactions you’ve had in classes.
- Try to inculcate extracurricular activities and soft skills in your LOR, as these are invaluable skills.
Pre-Intern Preparation
Having no prior experience, one struggles a lot initially. Not having any project or internship experience, I learned about data science and R before the internship. Most of the professors who hire interns are looking for preliminary work in the field like research and analysis; thus, having research skills is a bonus for application, although lack of them won’t hold you back.
Working and Experiencing Firsthand
My internship was 8 weeks long; in the initial 2–3 weeks, I read extensively about “genomics data” on which the theory is based; apart from acquiring skills in machine learning; the Post Doctorates readily helped in learning and discussing the theory for research.
After this, data pre-processing was done to filter and analyze data that would be of utmost use in the research leading to the application of models based on statistics and conventional approaches to get the results.
The penultimate week was extensively based on writing the manuscript and documentation. Adding to my work, I learned the most about python and machine learning during my internship. The best part was the discussions with the Professor, as such interactions are not present in corporate internships. It’s an enlightening experience to have one-on-one interaction with professors regularly.
Learnings and Advice
This was my first internship, and advice for anyone going for an internship would keep their expectations low. Don’t stress out on the utility and future, rather enjoy the experience. Make sure to enjoy the work and learn the new subject.
This will enhance your interest in the field and clarify whether you want to work in academia or not, for your first internship helps you prepare for future opportunities.
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