Houston, TX, 77007, USA
287 days ago
Postdoctoral Fellow - Computational Precision Oncology
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 project seeking postdoctoral fellows focuses on cancer patient digital twins, especially establishing image-guided mechanistic mathematical models to predict and optimize cancer (e.g., breast cancer, glioma, colorectal cancer, sarcoma) treatment response on a patient-specific basis. *LEARNING OBJECTIVES* The 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, 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. All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations. *ELIGIBILITY REQUIREMENTS* Applicants should have earned a Ph.D. in one of the applied mathematics, natural sciences, computer sciences, engineering, or related fields. Experience with mathematical modeling, computational sciences, 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. *POSITION INFORMATION* MD Anderson offers full-time postdoc positions with a [salary ranging from $64,000 to $76,000](https://trainees.mdanderson.org/apply/mdaPostdoctoralFellowStipendFY24.pdf). depending on the number of years of postgraduate experience. The University of Texas MD Anderson Cancer Center offers excellent [benefits](https://www.utsystem.edu/offices/employee-benefits/insurance-0/eligibility), including medical, dental, [paid time off](https://www.mdanderson.org/about-md-anderson/employee-resources/leave.html), [retirement](https://www.utsystem.edu/offices/employee-benefits/ut-retirement-program/voluntary-retirement-programs), tuition benefits, educational opportunities, and individual and team recognition. 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](http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html)
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