2027 Future Talent Program – Translational Sciences and Outsourcing – Intern (AI/ML)

Location: South San Francisco, California, United States of America; US and Puerto Rico residents only.

Salary range: $39,108–$111,111 per year.

Company

hirify.global is a pharmaceutical research organization developing medicines through drug discovery and development.

What you will do

• Analyze large-scale pharmacokinetic and molecular datasets and prepare reproducible modeling and evaluation workflows.
• Implement and benchmark classical machine learning, molecular-structure-based, time-series, and mechanism-informed methods for pharmacokinetic curve prediction.
• Design random, scaffold, time-based, and chemical-similarity-aware evaluation settings and assess compound novelty, data leakage, and prospective generalization.
• Collaborate with scientists to interpret results and ensure scientifically meaningful benchmark conclusions.
• Document methods and results, contribute to a draft manuscript or technical report, and present 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 such as ICML, ICLR, or NeurIPS.
• Strong Python programming skills and experience with machine learning or deep learning frameworks such as PyTorch or similar tools, including model development and evaluation.
• Ability to work with complex scientific datasets, build reproducible analysis pipelines, and understand how data leakage and evaluation design affect model generalization.
• Demonstrated interest in preparing a publishable computational drug discovery benchmark, including comparative study design, reproducible research workflows, and clear interpretation and communication of technical results.
• Strong communication skills and ability to summarize technical results clearly.

Nice to have

• Experience with pharmacokinetics, pharmacometrics, ADMET, or drug discovery.
• Familiarity with concentration–time curves, AUC, Cmax, clearance, half-life, compartment models, and NCA.
• Experience with SMILES, molecular fingerprints, graph neural networks, Chemprop, Uni-Mol, or RDKit; familiarity with molecular property prediction, QSAR, or ADME modeling.
• Experience with Tanimoto similarity, scaffold splitting, chemical series clustering, or out-of-distribution evaluation.
• Experience with time-series modeling, ODE models, neural ODEs, or physics-informed machine learning.

Culture & Benefits

• Fixed-term internship lasting up to 12 weeks with one or more research projects.
• Exposure to pharmacokinetics, computational drug discovery, molecular representations, chemical similarity analysis, and benchmark design.
• Opportunities for reproducible research and cross-functional collaboration within a pharmaceutical research organization.
• Development of scientific writing, communication, and presentation skills.
• Expected deliverables include a documented evaluation workflow, final presentation, and draft manuscript subject to internal publication review.