Internship Application Resources

As part of my Ph.D., I decided to do a 3-month internship after my third year. While going through the application process, I learned a lot and would like to share this information with others.

The information below reflects my experience and opinions and is most helpful for Computational Biology or Computer Science (CS) students interested in the combination of tech and biology.

Why do an internship?

• Research and Technical Skills
  • Gain hands-on experience working with cutting-edge tools and technologies that may not be available in academia.
  • Some companies have larger and more diverse datasets, enabling projects that are not as feasible in academia.
  • Opportunity to refine coding skills and computational techniques.
• Career Development and Industry Exposure
  • Network with industry experts; many internship programs facilitate networking events with employees across different teams
  • Build connections that can help with your post-PhD job search
  • See how your skills apply outside of academia, allowing you to assess whether you enjoy industry work
• Funding and Collaboration
  • Some internships can lead to long-term collaborations between your PhD lab and the company, with potential publications. However, this depends on the company

Different internship roles applicable for Computational Biology students

• Bioinformatics Scientist: Develops algorithms, pipelines, and statistical models for analyzing biological data (e.g., genomics, transcriptomics, proteomics)
• Computational Biologist: Applies computational techniques to study biological processes, often in drug discovery, functional genomics, and precision medicine
• Machine Learning Scientist: Develops AI/ML models for drug discovery, biomarker discovery, medical imaging, or synthetic biology
• Data Scientist: Applies data science and statistics to clinical trials, real-world patient data (RWD), electronic health records (EHR), and omics data.
• Quantitative Researcher: Develops mathematical, statistical, and computational models to analyze and predict outcomes. This applies to biology, healthcare, and even finance.

Resume differences between industry vs academia

• Industry resumes are much shorter and concise (1-2 pages max)
• Tailor your resume for each role you apply to—ensure keywords from the job description are included
• I also recommend reaching out to your universities career center as most universities have mentors that can help tailor your academic CV to an industry resume

How do I apply to internships?

Preparation

• Talk to your PhD advisors early. Be transparent about your internship plans. I discussed mine a month before applying, explaining why I wanted an internship and how it would benefit my PhD. Some advisors may want you to complete specific milestones (e.g., qualifying exam, paper submission) beforehand.
• If you’re an international student, consult your university’s International Student Office about work authorization requirements (CPT, OPT).
• Update your CV/resume with recent projects and skills—this makes fine-tuning for each application easier.
• Identify what you want from an internship. Do you want to improve ML skills, gain industry exposure, or work with large datasets? Knowing this helps filter opportunities.
• Start preparing for technical assessments if you’re applying to computational roles; Leetcode or similar tools are very helpful.
• Create a LinkedIn profile if you do not already have one. It’s great for finding internships, connecting with employees, and staying updated on opportunities. I also invested in a LinkedIn+ subscription, which allows you to message other LinkedIn users without being connected and provides insights into how well your profile aligns with specific roles.
• Build a personal website. This helps showcase projects, skills, and publications. I use (academicpages.github.io)[https://github.com/academicpages/academicpages.github.io] (a free template).
• Track your applications. Use a Google Sheet or Excel file to organize positions, deadlines, and statuses. You can view my tracking format here.

Application process

• Use LinkedIn job alerts—this emails you new postings daily. I set alerts for Computational Biology, Bioinformatics, Biostatistics, Machine Learning, and Data Science internships.
• Track open positions and fine-tune your resume before submitting applications.
• Reach out to employees at companies you’re interested in for coffee chats. I connected with people via LinkedIn and my university’s alumni network, which gave me insight into different roles and company cultures.

Interview process

If you’ve been invited to interview—congratulations! Here’s what to expect (from my experience):

Types of interviews

• Pre Screening: Often required for coding-heavy roles. You’ll be given a time-limited technical challenge. Prepare using Leetcode or similar tools.
• HR screening: A short (15-30 min) call to confirm your background, interests, and availability.
• Hiring manager interview: The questions asked during this type of interview varies and can range from behavioral questions to more technical focused one.
  • Introduce yourself with a concise elevator pitch.
  • Be ready to describe 1-2 PhD projects in detail.
  • Expect follow-up technical questions related to your research.
  • Prepare to explain why you’re interested in this role and company.
• Technical Interview: The technical interviews really depend on the role you are applying to. The format also varies from virtual live coding session to at home coding assessments. Again, Leetcode is a great resource to prepare for these kind of interviews.

Things to keep in mind as an international student

There are two work authorizations as part of an F1 visa that allow you to do an internship outside of the university where you are doing your PhD:

1. Curricular Practical Training (CPT): Must be completed before graduation and does NOT reduce your post-PhD OPT time.
2. Optional Practical Training (OPT): Can be used before or after graduation but has a limited duration (12-36 months, depending on STEM status).

Why does this matter? If you plan to work in the U.S. after graduation, you might want to preserve OPT time by using CPT for your internship. Always check with your university’s International Student Office before applying for internships! Here is a guide for Brown University students.

Final Thoughts

Applying for an internship takes time and effort, but it’s an extremely rewarding experience. It allows you to build industry skills, expand your network, and explore new career paths while still in academia.

If you have any questions or experiences to share, feel free to connect with me!

Other Resources

• Microsoft Research Internship Resource from Alex Lu (Senior Researcher at MSR)