AI-Driven Translational Sciences Co-op: PK/TK Modeling

MSD; Boston (MA); Hybrid; USD 39,000 - 111,000; Part time

Job summary

MSD’s Future Talent Program offers a 6-month co-op in our Research and Development Division, featuring translational modeling and AI-enabled exposure prediction across preclinical dose levels.

You will join the Translational Sciences and Outsourcing (TSO) team within PDMB, collaborating with Data Science, PKPD, DMPK, and preclinical toxicology to apply modern AI/ML methods to PK/TK data with direct relevance to study design and therapeutic window assessment.

Qualifications

• Currently pursuing a Master’s or Ph.D. in a quantitative field (data science, CS, applied math, statistics, computational chemistry, biomedical engineering, or related).
• Experience with ML, statistical modeling, scientific computing, or computational modeling.

Responsibilities

• Curate and quality-check preclinical cross-dose PK/TK datasets with provenance and holdout splits.
• Conduct TK analyses with endpoints like AUC and Cmax across dose groups and routes of administration.
• Develop and benchmark AI-enabled and hybrid models against baselines like linear scaling and QSAR methods.
• Evaluate model performance and uncertainty, including nonlinear PK behaviors.
• Create visualizations and write clear summaries for cross-functional stakeholders.
• Share outcomes via internal/external presentations and publications.

Skills

Python programming

Deep learning frameworks

ML/statistical modeling

Data visualization & communication

Cross-functional collaboration

Education

Master’s or Ph.D. in data science/CS/related field

Tools

NumPy

pandas

scikit-learn

PyTorch

JAX

Job description

MSD’s Future Talent Program offers a 6-month co-op in our Research and Development Division, featuring translational modeling and AI-enabled exposure prediction across preclinical dose levels.

You will join the Translational Sciences and Outsourcing (TSO) team within PDMB, collaborating with Data Science, PKPD, DMPK, and preclinical toxicology to apply modern AI/ML methods to PK/TK data with direct relevance to study design and therapeutic window assessment.