Postdoctoral Fellow, AI Driven Precision Oncology

Job Posting

Title:

Postdoctoral Fellow, AI Driven Precision Oncology

Hiring Department: Department of Medicine

Position Open To: All Applicants

Weekly Scheduled

Hours:

40

FLSA Status: Exempt

Earliest

Start Date:

Immediately

Position Duration: Expected to Continue Until Aug 31, 2029

Location: UT MAIN CAMPUS

This is a grant funded position with an end date 1 year from the start date. The position is renewable based upon availability of funding, work performance, and progress toward goals with the option to continue until August 31, 2029 if renewed.
Note:
This candidate must be authorized to work in the United States without sponsorship.

The Kowalski Lab at the University of Texas at Austin invites applications for a Postdoctoral Fellow position focused on developing advanced, AI-enabled methods for clinical decision support in precision oncology. 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.

The lab leads multi-institutional projects combining clinical, molecular, proteomic, and other published data to build explainable and scalable decision-support systems. These systems are designed to bridge gaps in personalized treatment for patients with rare, resistant, or genomically un-targetable cancers.

• 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.
• Lead and co-author high-impact publications and grant proposals.
• Collaborate with clinicians, bioinformaticians, and data scientists across UT Austin, and other partners.
• Mentor graduate and undergraduate research assistants and contribute to lab leadership.

• Develop and deploy innovative AI models for treatment discovery and patient-specific decision support.
• Gain experience in translational research across clinical, academic, and technology domains.
• Participate in lab initiatives aligned with NCI, CPRIT, and NIH-funded projects.

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. Proficiency in Python and R for use in data science and modeling. Excellent writing and communication skills;

demonstrated publication record.

Knowledge of cancer biology, clinical oncology workflows, or multi-omics data.

$62,232+ depending on NIH level

• Standard office equipment
• Repetitive use of a keyboard

• Resume/CV
• 3 work references with their contact information; at least one reference should be from a supervisor
• Letter of interest

The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.