The Department of Radiation Oncology at the University of Maryland School of Medicine is seeking one or more highly motivated postdoctoral fellows to perform cutting-edge research in AI for radiation therapy. Research areas include developing and implementing AI techniques for image-guided radiation therapy, such as image reconstruction, processing, synthesis, and registration, as well as AI for treatment outcome prediction and clinical decision making. The projects will involve using multi-modality images (CT, CBCT, MRI, PET, Ultrasound) and clinical software in radiation therapy such as treatment planning and image guidance tools. The overall goal of the research is to develop practical AI technologies that can directly benefit patient care in radiation therapy.

Training and Career Path

This is a 2-3 year, full-time, mentored research position. The successful candidate will receive regular mentorship and evaluation, be trained and encouraged to disseminate research findings in major national conferences and peer-reviewed publications, and to seek extramural research funding.

The trainee can pursue an academic, industry, or clinical professional career afterward. The Radiation Oncology department has a CAMPEP approved Medical Physics certificate program. The postdoc fellow will have the option to enroll in the certificate program with the tuition waived upon satisfactory performance. Finishing the certificate program will render the candidate eligible for medical physics residency training and become a clinical medical physicist or faculty afterward.

More information about a clinical medical physics career can be found on the following website:

https://w3.aapm.org/medical_physicist/index.php

Medical physicists are well-paid and stable professionals, and they are the only non-MD professionals certified by the American Board of Medical Specialties (ABMS). Medical physicists collaborate with physicians closely in patient imaging, treatment planning and delivery, and quality assurance in routine clinical practice.

Research Lab and Environment

The new member will work under the supervision of Dr. Lei Ren, who is a Professor and Associate Chief of Physics Research at the University of Maryland and an adjunct Professor at Duke University. Dr. Ren's group works on AI-based radiotherapy research with a strong focus on clinical translation. His research has been funded by multiple NIH R01 grants and industry grants with awards from AAPM and ASTRO. Dr. Ren is a Fellow of AAPM. Details about Dr. Ren's profile can be found at the following link:

https://www.medschool.umaryland.edu/profiles/Ren-Lei/

Equipment includes a computer cluster with high-end GPUs, and state-of-the-art radiotherapy systems including Varian Truebeam and Edge linacs, multi-vault Proton Therapy machines at Maryland Proton Treatment Center (MPTC) with over 3000 patients treated, Raysearch and Eclipse treatment planning systems, CBCT and VisionRT surface photogrammetry. The Department of Radiation Oncology has consistently ranked among the top 10 of NRG Oncology's main member sites worldwide in terms of patient enrollments for clinical trials, and was tied for the number two ranking as of 2021. Our physicians, physicists, and basic science researchers are nationally recognized leaders in discovering new and better ways to treat cancer with radiotherapy. The department also has a successful track record of commercialization of research products.

Application Process

The position will remain open until suitable candidates are found. Please submit CV and a letter of interest through this website:

Qualifications and Skills

Ph.D. in Medical Physics, Physics, Mathematics, Electrical Engineering, Computer Science, Biomedical Engineering, or a related field is required. Expertise is required or highly desired in one or more of the following areas: algorithms, analytical derivation, data analysis, coding, or mathematical modeling. Strong programming skills are highly desired. The candidate should demonstrate strong motivation in pursuing research developments in the medical field.