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Medical Imaging Machine Learning Postdoc Jobs (NOW HIRING)

MD Anderson

Postdoc Fellow - Imaging Physics

Houston, TX · On-site

$46K - $63K/yr

A postdoctoral fellowship position is available in the Department of Imaging Physics in the ... Experience with machine learning and deep learning techniques, mathematical modeling, or medical ...

MD Anderson

Postdoc Fellow - Imaging Physics

Houston, TX · On-site

$46K - $63K/yr

A postdoctoral fellowship position is available in the Department of Imaging Physics in the ... Experience with machine learning and deep learning techniques, mathematical modeling, or medical ...

MD Anderson

Postdoc Fellow - Imaging Physics

Houston, TX

$46K - $63K/yr

A postdoctoral fellowship position is available in the Department of Imaging Physics in the ... Experience with machine learning and deep learning techniques, mathematical modeling, or medical ...

University at Buffalo

Postdoctoral Associate

Buffalo, NY · On-site

$60K/yr

Posting Details Position Information Fiscal Year 2026-2027 Position Title Postdoctoral Associate ... medical imaging research. • Experience developing artificial intelligence and machine learning ...

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Postdoc Fellow - Imaging Physics

Houston, TX • On-site

MD Anderson
Health Care and Social Assistance • 10K+ employees
Learn more about MD Andersonexternal

$46K - $63K/yr

Full-time

Re-posted 20 days ago

Key responsibilities

  • Engage in interdisciplinary research projects involving image-guided computational modeling, deep learning, and image analysis related to cancer diagnosis and treatment.

  • Develop and validate image processing methods and image-guided models to investigate tumor growth, treatment response, and tumor microenvironment.

  • Communicate research findings through reports, presentations, and publications, and participate in seminars and academic conferences.

MD Anderson Cancer Center rating

8.5

Company rating: 8.5 out of 10

Based on 172 frontline employees who took The Breakroom Quiz

Job description

A postdoctoral fellowship position is available in the Department of Imaging Physics in the laboratory of Chengyue Wu, PhD. Dr. Chengyue Wu's research interests focus on computational precision oncology, especially integrating computational/mathematical approaches with emerging biomedical imaging techniques to improve the diagnosis, prognosis, and treatment of human cancers.

Dr. Wu has extensive experience on developing and validating image processing methods and image-guided models for investigating tumor growth and treatment response, tumor-associated vasculature and microenvironment, and drug delivery. The lab is in a highly collaborative research environment with access to world-class resources, expertise, and data.

Current projects seeking postdoctoral fellows include: Image-guided computational modeling ("digital twins") to predict and optimize cancer (especially breast cancer) treatment response on a patient-specific basis. Development of deep learning models, longitudinal image analysis, and multi-modality data integration to improve breast cancer early detection. LEARNING OBJECTIVES This postdoctoral fellow will engage in highly productive interdisciplinary research projects in image-guided precision oncology and personalized cancer healthcare.

The fellow will expand their knowledge and skills in quantitative imaging, image analysis, artificial intelligence (AI)/deep learning technologies, mathematical biomechanical modeling, inverse problems, and uncertainty quantification. The fellow will have opportunities to contribute to ongoing research projects and will be encouraged to explore and develop new areas of research interest with guidance from the mentor. The fellow will be expected to work closely with research/clinical collaborators, communicate findings via reports, abstracts, presentations, and publications, and actively participate in seminars, conferences, and related academic endeavors.

ELIGIBILITY REQUIREMENTS Applicants should have earned a Ph.D. in one of the natural sciences, computer sciences, applied mathematics, engineering, or related fields or a medical degree. Experience with machine learning and deep learning techniques, mathematical modeling, or medical image analysis is preferred

Applicants do not need to be US citizens or permanent residents. This appointment is not part of a clinical training program; individuals holding an M.D. degree or equivalent are not permitted to engage in patient care activity

ADDITIONAL APPLICATION INFORMATION The trainee will be appointed for one year from the date of hire with an option to be renewed for up to three years. POSITION INFORMATION Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements. This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening

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. 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 FACULTY MENTOR Dr

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