2027 Future Talent Program – Translational Sciences and Outsourcing – Co-op

Merck · Boston (MA Parcel B Laboratory), MA

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Role summary

Merck seeks a graduate student for a 6-month co-op in the Translational Sciences and Outsourcing team. The role focuses on developing AI/ML models to predict drug exposure in preclinical studies, combining data curation, machine learning, and scientific communication to support pharmacokinetics and safety decision-making.

What they're looking for

Currently pursuing Master's or Ph.D. in data science, computer science, applied mathematics, statistics, or related quantitative field
Research experience in machine learning, statistical modeling, scientific computing, or computational modeling
Strong Python programming with NumPy, pandas, and scikit-learn
Experience with deep learning frameworks such as PyTorch or JAX
Proficiency in machine learning, statistics, model evaluation, and reproducible analysis workflows
Ability to analyze messy tabular or time-series data and communicate findings clearly
Effective written and verbal communication skills for cross-functional collaboration

What you'll be doing

Curate and quality-check preclinical toxicokinetics datasets with clear provenance and appropriate data splits
Conduct toxicokinetics analysis on exposure endpoints to identify trends, nonlinearities, and data limitations
Develop and benchmark AI-enabled and hybrid modeling approaches against empirical and mechanistic baselines
Evaluate model performance, uncertainty estimation, and ability to detect nonlinear pharmacokinetics behavior
Create visualizations, written summaries, and presentations for cross-functional stakeholders

Compensation$39,108–$111,111

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Date posted4 days ago

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