Grad Intern – Target Safety Risk Weighting and Evaluation Strategies

🔥 18 hours ago

🇺🇸 United States – Remote

💵 $35 - $41 / hour

⏰ Full Time

⚪️ Entry-level

🎲 Risk

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Amgen

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1980

🏥 Healthcare

🧬 Biotechnology

💊 Pharmaceuticals

💰 $28.5G Post-IPO Debt on 2022-12

Healthcare • Biotechnology • Pharmaceuticals

Amgen is a global leader in biotechnology, focusing on the development and commercialization of innovative medicines made from living cells. The company aims to treat serious illnesses, often targeting diseases with limited therapeutic options. Amgen emphasizes scientific innovation and is committed to ethical research, patient safety, and environmental sustainability. It actively engages in clinical trials and is known for its contributions to the fields of cancer treatment and obesity management among others.

📋 Description

• Design and integrate tools that accelerate safety assessments from early discovery through post-marketing • Build workflows that ingest molecular -omics datasets, clinical adverse event data, and internal pre-clinical model data • Surface mechanistic insights and score or weight potential safety concerns • Support non-clinical safety strategy in collaboration with toxicologists, clinical safety scientists, computational biologists, and data engineering partners • Use and refine AI tools for data aggregation, processing, interpretation, and automated report generation • Integrate public and internal multimodal data, including omics, preclinical findings, clinical safety signals, and real-world evidence, into risk-scoring methods • Generate mechanistic off-target hypotheses and pathway-level safety rationales • Write documentation covering methods, assumptions, and limitations • Contribute to the Target Safety Scoring Assessment codebase • Present progress and findings to TSRS stakeholders and incorporate feedback • Collaborate with TSRS team members to prioritize high-impact use cases

🎯 Requirements

• Must be available to work a full-time schedule • Expected continued enrollment in an accredited college or university following the internship program / co-op • Student must be located in the United States for the duration of the internship program • Must be 18 years or older • Graduated with a bachelor’s degree from an accredited college or university • Currently enrolled in an MBA program for an MBA internship, Master’s program for a Master’s internship, PharmD program for a PharmD internship, or Ph.D. program for a PhD internship • Must complete the first year of the applicable graduate program before the internship starts • Degree concentration in Toxicology, Computational Biology, Bioinformatics, Computer/Data Science, Life Sciences, or a related field preferred • Completion of at least 1 year of graduate study by the start of the internship preferred • Proficiency in Python and R for data analysis and modeling, including pandas/NumPy/scikit-learn and tidyverse/Bioconductor • Proficiency with AI coding tools such as Codex and Claude • Experience with Jupyter/R Markdown, SQL, Git/GitHub, and environment management • Coursework or hands-on projects in AI/ML; familiarity with NLP/LLMs, prompt engineering, retrieval-augmented generation, and summarization • Experience with -omics datasets and biological knowledge bases/ontologies such as GO and MedDRA, and public biology resources such as Open Targets or similar • Comfort integrating heterogeneous preclinical, clinical, and literature data and mapping to pathways/phenotypes • Familiarity with target safety assessment, off-target mechanisms, and translational safety principles • Familiarity with APIs or simple workflow orchestration; basic cloud literacy, with AWS as a plus • Experience building dashboards or internal utilities such as Shiny is a plus • Candidates must be authorized to work in the U.S. for the duration of the program • Sponsorship for future FTE roles is not guaranteed

🏖️ Benefits

• Real-world impact through tools that inform target safety assessments and decision-making • End-to-end experience from problem scoping and data ingestion to evaluation, validation, and communication • Exposure to translational safety science, mechanistic biology, real-world datasets, multi-omics datasets, and literature evidence • Regular mentorship and feedback from TSRS scientists, data scientists, and engineers • Opportunities to present to stakeholders • Mentored research experience in a collaborative, mission-driven team • Competitive benefits • Collaborative culture • Professional and personal growth and well-being support • Executive and social networking events • Community volunteer projects • Inclusive culture valuing diversity of thought and experience • Reasonable accommodation for individuals with disabilities • Full-time internship opportunity

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