About the role#
This internship is part of the 2027 Future Talent Program within the Translational Sciences and Outsourcing team. You will work within the Pharmacokinetics, Dynamics, Metabolism, and Bioanalytics department. The role focuses on developing and benchmarking AI and machine learning methods to predict pharmacokinetic concentration-time profiles using large-scale internal datasets. This is a full-time, paid, 12-week summer position.
What you'll do#
- Analyze large-scale pharmacokinetic and molecular datasets and prepare them for reproducible modeling and evaluation.
- Implement and benchmark classical machine learning baselines, molecular-structure-based models, and time-series or mechanism-informed approaches for pharmacokinetic curve prediction.
- Design and compare random, scaffold, time-based, and chemical-similarity-aware evaluation settings.
- Quantify model performance across compound novelty levels to identify data leakage and generalization limitations.
- Collaborate with scientists to interpret results and ensure benchmark conclusions are scientifically meaningful.
- Document methods and results to contribute to a draft manuscript or technical report.
- Present your project outcomes at the end-of-summer intern symposium.
What you'll need#
- Current enrollment in a PhD program for computational chemistry, cheminformatics, machine learning, computer science, computational biology, statistics, or a related field.
- A strong record of publication in top-tier, peer-reviewed scientific journals or machine learning conferences.
- Strong Python programming skills and experience with machine learning or deep learning frameworks such as PyTorch.
- Experience with model development, evaluation, and building reproducible research workflows.
- Ability to work with complex scientific datasets and understand how data leakage and evaluation design affect model generalization.
- Strong communication skills to summarize technical results clearly.
- Demonstrated interest in preparing a publishable computational drug discovery benchmark.
Location & details#
- Location: South San Francisco, California, United States.
- Modality: On-site.
- Term: Summer 2027.
- Employment: Full-time intern.
About MSD
MSD is a pharmaceutical manufacturing company founded in 1891. It develops medicines and vaccines for both humans and animals. The organization operates globally and maintains its headquarters in Rahway, New Jersey. It employs over 39,000 people.
How to get in at MSD
Applying to MSD early provides a distinct advantage because recruiters often review the first wave of candidates before the applicant pool becomes unmanageable. Intern Insider sends an instant alert the moment a role matching your target is published anywhere, so you apply among the first and get seen before the pile grows. Reaching out to the right person can help your application stand out from the crowd. Intern Insider surfaces the recruiters behind the company roles so you can reach out directly to ask about the position or a referral, which materially improves your response rates.
