Pharmacokinetics AI/ML Intern — Benchmark & Discovery

Merck; South San Francisco (CA); On-site; USD 39,000 - 111,000; Full time

Job summary

Merck in South San Francisco, CA invites a highly motivated PhD student to join the Translational Sciences and Outsourcing Data Science team for a 12-week internship in AI/ML applied to pharmacokinetic modeling. You will benchmark methods, work with scientists, and contribute to reproducible research and a draft manuscript.

The role involves data preparation, implementing baselines, designing evaluation strategies, and presenting results at the summer end. Opportunity for publication exists.

Qualifications

• PhD student in computational chemistry, cheminformatics, machine learning, computer science, computational biology, statistics, or a related field.
• Strong publication record in peer-reviewed journals or ML conferences (e.g., ICML, ICLR, NeurIPS).
• Experience with reproducible research workflows and communicating technical results clearly.

Responsibilities

• Analyze large-scale pharmacokinetic and molecular datasets and prepare them for reproducible modeling and evaluation.
• Implement and benchmark classical ML baselines, molecular-structure-based models, and time-series or mechanistic approaches for PK curve prediction.
• Design evaluation settings (random, scaffold, time-based, chemical similarity) and assess generalization across data sources.
• Collaborate with scientists to interpret results and contribute to a draft manuscript or technical report.
• Present project outcomes at the end-of-summer intern symposium.

Skills

Python programming

ML benchmarking

Publishable research

Data preprocessing

Education

PhD student in computational chemistry/cheminformatics/ML/CS/bioinformatics

Tools

PyTorch

RDKit

Chemprop

Uni-Mol

Job description

Merck in South San Francisco, CA invites a highly motivated PhD student to join the Translational Sciences and Outsourcing Data Science team for a 12-week internship in AI/ML applied to pharmacokinetic modeling. You will benchmark methods, work with scientists, and contribute to reproducible research and a draft manuscript.

The role involves data preparation, implementing baselines, designing evaluation strategies, and presenting results at the summer end. Opportunity for publication exists.