Postdoctoral Fellow, Ai Driven Precision Oncology

The University of Texas at Austin

Austin, TX, US
$62,232 + depending on nih level py
On-site
Ai models for treatment discovery
Multi-modal data integration
Explainable ai
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.
  • Collaborate with clinicians, bioinformaticians, and data scientists across UT Austin, and other partners.

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

Skills & Requirements

Must-have

  • AI models for treatment discovery
  • multi-modal data integration
  • explainable AI
  • Python and R proficiency
  • translational research

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 related field
  • PhD 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

Authorized to work in the United States without sponsorship

Tailored Resume

Cover Letter