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About the Role

This internship in the Translational Sciences and Outsourcing (TSO) Data Science team focuses on developing and benchmarking AI/ML methods for pharmacokinetic curve prediction. The role offers an opportunity to apply modern AI/ML to pharmaceutical data, learn about computational method evaluation in an industrial research setting, and contribute to a publication-oriented study.

Responsibilities

Analyze and prepare large-scale pharmacokinetic and molecular datasets 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 various evaluation settings (random, scaffold, time-based, chemical-similarity-aware) to quantify performance across compound novelty levels.
Collaborate with scientists to interpret results and ensure scientific meaningfulness of benchmark conclusions.
Document methods and results, and contribute to a draft manuscript or technical report.
Present project outcomes at the end-of-summer intern symposium.

Requirements

PhD student in computational chemistry, cheminformatics, machine learning, computer science, computational biology, statistics, or a related field.
Strong publication record in top-tier, peer-reviewed scientific journals or machine learning conferences (e.g., ICML, ICLR, NeurIPS).
Strong Python programming skills with experience using machine learning or deep learning frameworks (e.g., PyTorch).
Experience with model development and evaluation.
Ability to work with complex scientific datasets, build reproducible analysis pipelines, and understand data leakage and evaluation design effects on model generalization.
Demonstrated interest in preparing a publishable computational drug discovery benchmark.
Experience in designing comparative studies, building reproducible research workflows, and interpreting/communicating technical results.
Strong communication skills for summarizing technical results clearly.

Skills

Python
Machine Learning
Deep Learning
PyTorch
Reproducible Research
Data Analysis
Scientific Writing
Communication
Pharmacokinetics
Pharmacometrics
ADMET
Drug Discovery
Molecular Representations
Cheminformatics
Graph Neural Networks
Chemprop
Uni-Mol
RDKit
QSAR
ADME Modeling
Molecular Similarity Analysis
Tanimoto Similarity
Scaffold Splitting
Chemical Clustering
Out-of-Distribution Evaluation
Time-Series Modeling
ODE Models
Neural ODEs
Physics-Informed Machine Learning

Location

Work Type

Intern/Co-op
Fixed Term

Experience Level

PhD student

Education Level

Salary/Compensations

$39,108 - $111,111

Benefits

Development opportunities
Chance to see if the company is the right fit for long-term goals
Exposure to pharmacokinetics and its applications in drug discovery
Learning machine learning methods for concentration-time curve prediction
Understanding molecular representations, similarity analysis, chemical clustering, and rigorous benchmark design
Gaining experience in reproducible research and cross-functional collaboration
Developing scientific writing, communication, and presentation skills

About the Company

The Future Talent Program features internships that last up to 12 weeks and will include one or more projects.
This position may be closed before the posted end date or may remain open longer, at the discretion of the company.
Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities.
We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds.
The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment.
We encourage our colleagues to respectfully challenge one another’s thinking and approach problems collectively.

Equal Opportunity

Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities.
As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics.
As a federal contractor, we comply with all affirmative action requirements for protected veterans and individuals with disabilities.
For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit: EEOC Know Your Rights EEOC GINA Supplement
Learn more about your rights, including under California, Colorado and other US State Acts
San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance
Los Angeles Residents Only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance