Target Safety Scoring Intern – AI & Omics

Amgen Inc.; Thousand Oaks (CA); Hybrid; USD 49,000 - 57,000; Full time

Job summary

Amgen Inc. in Thousand Oaks, CA is offering a Grad Intern position in Target Safety Risk Weighting and Evaluation Strategies for Summer 2027.

You will design tools to accelerate safety assessments and surface mechanistic insights from omics, preclinical, and clinical data while collaborating with toxicologists and data engineers. Expect to work with Python, R, NLP/LLMs, and AI tools to build risk scoring methods, develop transparent documentation, and present findings to stakeholders.

Qualifications

• Degree in a relevant field and ongoing advanced degree in the specified programs.
• Strong programming in Python and R for data analysis and modeling.
• Experience with AI tools and NLP/Lang Models; familiarity with data integration.
• Experience with omics data, preclinical/clinical data, and literature resources.

Responsibilities

• Use and refine AI tools for data aggregation, processing, interpretation, and automated report generation.
• Integrate multimodal data into risk scoring/weighting methods for safety decisions.
• Generate mechanistic hypotheses and pathway-level safety rationales.
• Write documentation and contribute to codebase for Target Safety Scoring Assessment.
• Present progress to TSRS stakeholders and iterate on tools based on feedback.
• Prioritize use cases with maximum impact in collaboration with TSRS team.

Skills

Python

R

SQL

Git/GitHub

NLP/LLMs

AI tooling

Jupyter

R Markdown

Education

Bachelor’s degree

MBA/Master/PharmD/PhD in progress

Tools

Open Targets

Public biology resources

AWS

Jupyter

Job description

Amgen Inc. in Thousand Oaks, CA is offering a Grad Intern position in Target Safety Risk Weighting and Evaluation Strategies for Summer 2027.

You will design tools to accelerate safety assessments and surface mechanistic insights from omics, preclinical, and clinical data while collaborating with toxicologists and data engineers. Expect to work with Python, R, NLP/LLMs, and AI tools to build risk scoring methods, develop transparent documentation, and present findings to stakeholders.