Summer 2026 - Oncology Translational Bioinformatics Internship

Role Summary

Summer 2026 - Oncology Translational Bioinformatics Internship. A 10-week summer internship in Translational Informatics and Predictive Sciences, focusing on AI-powered multi-modal biomarker discovery to integrate peripheral biomarkers with clinical data for cancer treatment optimization. Work within an experienced cross-functional team to adapt contrastive learning approaches and translate neural network predictions into clinically actionable biomarker signatures. The internship supports early development and establishing AI-driven platforms for biomarker discovery across oncology programs.

Responsibilities

• Implement and adapt advanced deep learning frameworks for multi-modal biomarker discovery, customizing methodologies for clinical data requirements.
• Train and validate deep learning models on clinical trial datasets to identify predictive biomarkers for treatment response, incorporating both peripheral biomarkers and clinical variables.
• Develop model interpretability solutions to translate complex neural network predictions into clinically actionable and interpretable signatures.
• Conduct robust performance evaluations, benchmarking AI/ML models against existing biomarker approaches.
• Perform analysis and visualizations in a reproducible research framework, ensuring robust documentation of methodology and results.
• Deliver results and present findings to cross-functional teams for decision-making support.

Qualifications

• Master or PhD student enrolled in computational biology, bioinformatics, statistics, computer science, data science or related fields.
• Hands-on experience with deep learning frameworks, particularly TensorFlow and PyTorch, with experience in neural network architectures, tree-based models and ensemble modeling methods.
• Strong proficiency in Python (preferred) or R programming including libraries such as tidyverse, scikit-learn, pandas, and lifelines.
• Foundational understanding of oncology and cancer biology, with familiarity in clinical trial design and biomarker development processes.
• Authorized to work in the US for the duration of the internship; immigration or visa sponsorship is not available for this position.

Skills

• Deep learning and multi-modal data integration
• Model interpretability and biomarker signature development
• Clinical trial data analysis and biomarker discovery
• Python or R programming; data visualization and reproducible research practices

Education

• Master or PhD student in computational biology, bioinformatics, statistics, computer science, data science or related fields

Additional Requirements

• Temporary, time-bound internship with no guarantee of ongoing employment
• On-site/hybrid work arrangement determined by role; travel not specified as essential