$ 62,232 + depending on nih level; not specified; ...
Ai-enabled methods for clinical decision support
Integrating multi-modal data
Explainable and scalable decision-support systems
The fellow will work at the intersection of computational innovation, translational science, and patient-centered care, contributing to pioneering efforts in integrating multi-modal data for individualized cancer therapy selection
Job Summary
The fellow will work at the intersection of computational innovation, translational science, and patient-centered care, contributing to pioneering efforts in integrating multi-modal data for individualized cancer therapy selection.
Design and evaluate algorithms for treatment and response matching using integrated clinical and molecular datasets.
Develop knowledge graphs and multimodal embeddings for cancer patient digital twin construction.
Matching Summary
The fellow will work at the intersection of computational innovation, translational science, and patient-centered care, contributing to pioneering efforts in integrating multi-modal data for individualized cancer therapy selection.
Salary
$ 62,232 + depending on NIH level; Not specified; Not specified
Skills & Requirements
Must-have
AI-enabled methods for clinical decision support
integrating multi-modal data
explainable and scalable decision-support systems
Python and R for data science
Nice-to-have
cancer biology knowledge
clinical oncology workflows
multi-omics data experience
Key Requirements
PhD in computational biology, bioinformatics, computer science, information science, biomedical engineering, or a related field
PhD must have been received within the last three years
1 year of experience with machine learning, natural language processing, AI tools and frameworks, data integration, and/or explainable AI
Excellent writing and communication skills
demonstrated publication record
Work Rights
Must be authorized to work in the United States without sponsorship