Physics Postdoctoral Fellowship and Certificate Program
The Physics Postdoctoral Fellowship program began with the arrival of Dr. X. Allen Li to the Department of Radiation Oncology in 2004. Dr. Li saw the need for the training of postdoctoral fellows in the area of medical physics and recruited the first physics postdoctoral fellow to train in the Department of Radiation Oncology. Past Postdoctoral fellows performed in-depth research as well as received comprehensive clinical training. The Postdoctoral Fellowship program has had nine fellows graduate from the program.
2009 began the evolution of two separate medical physics training programs, the continuation of the Postdoctoral Fellowship Program and the creation of the new Physics Residency Program. While the Physics Residency Program is a three-year program with a focus on clinical training along with two research semesters, the Physics Postdoctoral Program is for PhD candidates who would like to focus primarily on research with limited and optional clinical physics classes and training.
Realizing the need for a formalized certificate training program, the Department of Radiation Oncology applied for CAMPEP accreditation of the curriculum offered to our postdoctoral fellows. The Physics Certificate Program was CAMPEP accredited in 2013. At this time, the Medical Physics Certificate Program is an internal program only offered to current radiation oncology postdoctoral fellows.
Postdoctoral Fellowship positions vary dependent on available research and research funding. Postdoctoral fellows completing the Physics Certificate Program are able to apply to any CAMPEP accredited Physics Residency programs.
Anyone interested in applying for a postdoctoral fellowship can send a copy of their CV to Jessica Kotowicz. All CVs are reviewed by Dr. X. Allen Li. Qualified applicants are then contacted for further discussion.
Medical Physics Certificate Program Statistics
|Year||Applicants in year
||Accepted in year
||Graduated in year
||Accepted to residency in year
||Employed in clinical setting in year
|| Employed in research setting in year
*Program accredited by CAMPEP December 2013
Working at the Medical College of Wisconsin
Why Work at MCW?
The Medical College of Wisconsin brings together the most inquisitive minds in science, medicine, education, and community engagement to solve the toughest challenges in health and society today. At the core of everything we do at the Medical College of Wisconsin is the pursuit of new knowledge and the power of academic medicine, where scientists, physicians and students work together with the community to ask the questions no one else is and fuel the continuous cycle of knowledge that’s shaping the future of medicine.
Why Work in Milwaukee?Milwaukee is one of the Midwest’s best-kept secrets and a prime location for the Medical College of Wisconsin’s main campus. We are more than just cheese and brats; we are home to a thriving music, sports and arts scene, Milwaukee’s rich history comes alive at any number of local museums or theatres, including our Historic Third Ward, the architectural landmark of the Pabst Mansion and the award-winning Milwaukee Riverwalk are just a few of the many attractions our city has to offer.
Living and Working in Milwaukee
Meet our Physics Postdoctoral Fellows
Silambarasan Anbumani, PhD
Research focused on prediction and assessment of radiation treatment response using quantitative imaging, CT biomarkers, and radiomics.
Renae Conlin, PhD
Research focuses on deep learning auto-segmentation models that concentrate on the auto-segmentation of abdominal anatomy based on MR images acquired during MR-guided adaptive radiation therapy.
Samira Dabaghmanesh, PhD
Research focused on extracting organ-specific radiobiological model parameters for selected abdominal and pelvic organs and to demonstrate their applications in determining OAR dose constraints.
Nguyen Phuong Dang, PhD
Research focused on auto-segmentation using deep learning models.
Juan Garcia Alvarez, PhD
Research focused on statistical methods for uncertainty estimation of deformable image registration-based dose accumulation, implementation in automated clinical workflows.
Saleh Hamdan, PhD
Research is focused on applying Deep Learning to generate radiation therapy plans accurately and efficiently for Real Time Adaptive Radiation Therapy using the MR-Linac.
Christina Sarosiek, PhD
Research focused on utilizing deep learning methods to automatically correct suboptimal auto-segmented contours on abdominal MR images to accelerate segmentation during MR-guided online adaptive radiotherapy.
Mohammad Zarenia, PhD
Research focused on developing auto-correction models for auto-segmented contours of abdominal organs to accelerate segmentation during MR-guided online adaptive radiotherapy.