2027 Future Talent Program – Translational Sciences and Outsourcing – Intern

Job Description

The Future Talent Program features internships that last up to 12 weeks and will include one or more projects. These opportunities in our Research and Development Division can provide you with great development and a chance to see if we are the right company for your long-term goals. We are seeking a highly motivated intern student to join the Translational Sciences and Outsourcing (TSO) Data Science team within our Pharmacokinetics, Dynamics, Metabolism, and Bioanalytics (PDMB) department. The intern will contribute to the development and rigorous benchmarking of AI/ML methods for pharmacokinetic curve prediction, partnering with scientists to generate insights that support decision-making across drug discovery and development. The ideal candidate will combine strong machine learning implementation skills with scientific rigor, reproducible research practices, scientific curiosity, and a collaborative mindset, along with an interest in AI, pharmacokinetics, cheminformatics, and computational drug discovery. This internship provides an opportunity to apply modern AI/ML to large-scale pharmaceutical data, learn how computational methods are evaluated in an industrial research setting, and contribute to a reproducible, publication-oriented study with potential impact across the PDMB research portfolio.

Project Overview

The intern will benchmark existing AI/ML methods for predicting pharmacokinetic concentration-time profiles using a large-scale internal dataset. The project will determine how model choice, data-splitting strategy, chemical similarity, compound novelty, and variation across data sources affect predictive performance and prospective generalization. The work is scoped to produce a rigorous, reproducible benchmark study and, subject to scientific results and internal review, a paper suitable for submission to a peer-reviewed journal or scientific conference.

Primary Responsibilities

Analyze large-scale pharmacokinetic and molecular datas