Postdoc: AI & RL for Adaptive Medical Imaging

University of Texas MD Anderson Cancer Center; Houston (TX); On-site; USD 64,000 - 76,000; Full time

Job summary

MD Anderson Cancer Center in Houston is seeking a postdoctoral fellow in the Department of Interventional Radiology, led by Iwan Paolucci, PhD, to advance machine learning and reinforcement learning for sequential medical decision making in adaptive imaging and treatment optimization.

The fellow will work with researchers and clinicians, publish findings, present at seminars and conferences, and contribute to ongoing projects across AI, imaging, and oncology using ML, RL, and Markov decision

Qualifications

• Ph.D. in natural sciences, computer sciences, data science, applied mathematics, engineering, or related field.
• Experience with ML, RL, deep learning, medical image analysis, or computational modeling preferred.
• Strong communication and collaboration with clinical and research partners.

Responsibilities

• Design and implement RL algorithms for sequential medical decision-making in imaging and treatment planning.
• Collaborate with clinical and research teams; present findings in reports and publications.
• Translate research into reproducible methods and contribute to seminars and conferences.

Skills

Reinforcement learning

Medical imaging

Machine learning

Sequential decision making

Job description

MD Anderson Cancer Center in Houston is seeking a postdoctoral fellow in the Department of Interventional Radiology, led by Iwan Paolucci, PhD, to advance machine learning and reinforcement learning for sequential medical decision making in adaptive imaging and treatment optimization.

The fellow will work with researchers and clinicians, publish findings, present at seminars and conferences, and contribute to ongoing projects across AI, imaging, and oncology using ML, RL, and Markov decision