Join the Kowalski Lab as a Postdoctoral Fellow to develop AI-driven methods for precision oncology. Contribute to groundbreaking projects that integrate multi-modal data for personalized cancer therapy.
Key Responsibilities
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
Required Qualifications
PhD in computational biology, bioinformatics, computer science, information science, biomedical engineering, or a related field
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