Postdoctoral Fellow - Imaging Physics

MD Anderson Cancer Center; Houston (TX); On-site; USD 50,000 - 70,000; Full time

Job summary

A prominent cancer research institution in Houston is seeking a Postdoctoral Fellow in Imaging Physics. This role focuses on computational research projects in image-guided cancer therapy, utilizing methodologies including deformable image registration and biomechanical modeling. Candidates should possess a Ph.D. in relevant fields, with experience in machine learning and deep learning techniques. The position offers a collaborative environment and opportunities to guide research initiatives. Competitive compensation and hybrid work arrangements may be available.

Qualifications

• Strong experience with machine learning and deep learning techniques.
• Familiarity with statistical modeling and image registration.
• Experience in computational research projects.

Responsibilities

• Engage in computational research projects in image-guided cancer therapy.
• Design and implement deformable image registration and biomechanical modeling.
• Guide research and clinical collaborations, disseminate findings.

Skills

Machine learning

Deep learning

Statistical modeling

Biomechanical modeling

Image registration

Data mining

Predictive modeling

Clustering

Classification

Education

Ph.D. in natural sciences, computer sciences, engineering, or related fields

Medical degree

Job description

Postdoctoral Fellow – Imaging Physics at MD Anderson Cancer Center (MDC). Join to apply for the Postdoctoral Fellow - Imaging Physics role in the Department of Imaging Physics led by Kristy Brock, Ph.D.

The Morfeus Lab (MD Anderson) researches deformable image registration algorithms, AI algorithms, biomechanical modeling, and image‑guided cancer therapy technologies, fostering strategic research collaborations and clinical translation. The lab offers a highly collaborative research training environment with state‑of‑the‑art imaging facilities.

Ongoing Projects Seeking Postdocs

• Image-guided liver surgery
• Image-guided head and neck surgery
• Cancer risk assessment and outcomes prediction using AI
• Validating in vivo imaging signals using correlative pathology
• Image-guided focal liver ablation
• Dose accumulation for personalized adaptive radiation therapy

Learning Objectives

The postdoctoral fellow will engage in computational research projects in image‑guided cancer therapy, including the design and implementation of deformable image registration, biomechanical modeling, and AI technologies. The fellow will expand knowledge and skills in imaging physics, data mining, predictive modeling, clustering, classification, and develop, train, and apply deep learning in large data environments. The fellow will guide research and clinical collaborations, integrate models into clinical workflow, coordinate with stakeholders, and disseminate findings via abstracts, posters, podium presentations, and publications.

Eligibility Requirements

Applicants must have earned a Ph.D. in one of the natural sciences, computer sciences, engineering, or related fields, or a medical degree. Experience with machine learning and deep learning techniques, statistical modeling, biomechanical modeling, or image registration and analysis is preferred.

Position Information

Off‑site work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements. The position may require maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code; routine reviews and screening may be required. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.

Faculty Mentor

Dr. Kristy Brock

Equal Employment Opportunity

It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html