Join the Kowalski Lab as a Postdoctoral Fellow, where you'll develop AI-driven methods for precision oncology, contributing to groundbreaking approaches in personalized cancer therapy. This role offers opportunities for innovation and collaboration in a dynamic research environment.
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
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 data science and modeling