Contract Opportunity: Bioinformatics & AI Scientist – Oncology Focus

We are seeking a contract Bioinformatics/AI Scientist for a leading biotech organization. This individual will work at the intersection of bioinformatics, machine learning, and oncology research, contributing to the development and benchmarking of cutting-edge AI models in biomedical data analysis.

Location:

• Remote (U.S. or Canada) or On-site in South San Francisco, CA
• Must be available to work during Pacific Time business hours

Contract Duration:

• Full-time through December, 2025

Core Requirements:

• PhD in Bioinformatics, Computational Biology, Computer Science, or a closely related discipline
• At least 6 years of hands-on experience in large-scale data processing (RNA-seq, WES), applying both traditional and advanced bioinformatics techniques
• Minimum 3 years of experience implementing and training machine learning models on omics data
• Deep understanding of cancer biology and/or clinical omics datasets
• Strong coding abilities in Python and shell scripting
• Proficiency with Git and high-performance computing environments
• Self-driven and results-oriented, capable of independently managing analyses and meeting project deadlines
• Excellent interpersonal and communication skills
• A strong curiosity for AI applications in pharma and a willingness to learn and innovate

Role Responsibilities:

• Collaborate with computational biology teams to evaluate AI/ML models across diverse preclinical and clinical multi-omics datasets
• Develop robust, scalable Python pipelines for benchmarking model performance on defined biomedical tasks
• Generate clear, insightful reports to communicate model effectiveness and propose optimization strategies
• Contribute to the standardization of workflows, ensuring reproducibility and rigor in analysis
• Provide feedback and suggest new directions to refine and enhance predictive modeling approaches

This is an exciting opportunity for a driven scientist to apply their skills in AI and bioinformatics to real-world clinical challenges in oncology. If you're passionate about science, data, and discovery, we’d love to hear from you.