Co-op in Translational PK/TK AI Modeling for Drug Safety

Merck; Boston (MA); Hybrid; USD 39,000 - 111,000; Full time

Job summary

Merck's Future Talent Program invites a motivated student to join the Translational Sciences and Outsourcing (TSO) team in PDMB for a 6-month co-op. Work on AI-enabled exposure prediction across dose levels in preclinical species, combining data curation, ML, and scientific communication to inform DMPK and NDS decisions.

You will collaborate with Data Science, PKPD, DMPK and toxicology teams while applying modern AI/ML methods to real PK/TK data with relevance to preclinical study design.

Qualifications

• Enrolled in a Master’s or Ph.D. program in a quantitative field.
• Experience with ML, statistical modeling, and scientific computing.

Responsibilities

• Curate cross-dose PK/TK datasets with provenance and holdout splits.
• Perform TK analysis using exposure endpoints (AUC, Cmax).
• Benchmark AI-enabled and hybrid models against baselines.
• Assess uncertainty and nonlinear PK behavior.
• Create clear plots and summaries for stakeholders.
• Share outcomes via presentations and publications.

Skills

Python

PyTorch

scikit-learn

NumPy

pandas

ML

data analysis

Education

Master's or PhD in data science or related quantitative field

Tools

KNIME

CS QE/QSAR tooling

ChemProp

Job description

Merck's Future Talent Program invites a motivated student to join the Translational Sciences and Outsourcing (TSO) team in PDMB for a 6-month co-op. Work on AI-enabled exposure prediction across dose levels in preclinical species, combining data curation, ML, and scientific communication to inform DMPK and NDS decisions.

You will collaborate with Data Science, PKPD, DMPK and toxicology teams while applying modern AI/ML methods to real PK/TK data with relevance to preclinical study design.