Radiological Sciences Training Grant


The Radiological Sciences Training Grant supports Ph.D. and postdoctoral research related to cancer. The goal of this training program is to prepare physicists and engineers for research careers in radiological physics and dosimetry as well as in functional, anatomical, and interventional medical imaging as it applies to the detection and treatment of cancer.

Faculty trainers in this program are committed to excellence in research broadly applied to cancer treatment, diagnosis, and prevention. We take a multi-disciplinary approach that is strongly image-science based and is increasingly molecular-focused. Trainees are immersed in this comprehensive research environment. Research training is available in every major area of physics involved with cancer treatment and diagnosis, cancer biology, and in emerging areas of molecular imaging.


Principal Investigator: Brian Pogue, Ph.D.
Principal Investigator: Bryan Bednarz, Ph.D.
Administrator: Carol Aspinwall


The Radiological Sciences Training grant supports 8 predoctoral trainees and 3 postdoctoral trainees. About 4-5 training grant openings are filled each year to replace individuals rotating off because of graduation or completion of training. Nominations for training grant positions are made by either the student’s advisor or the faculty advisor/sponsor in the case of postdoctoral nominations. Nominations include a description of the area of research, the cancer relevance, and an agreement that the student will fulfill the requirements of the training grant, detailed below. In most cases students must have reached dissertator status to be considered for a training grant position. To assure that a broad research area is included amongst trainees, faculty members will generally not have more than one advisee on the grant.

Application forms are available on the Medical Physics intranet (Net ID login required). An example pre-doctoral nomination is provided for reference.

Appointment Requirements

More details on the requirements for trainees can be found in the T32 Trainee Handbook.

  • Thesis research must be focused on the broad area of diagnosis, treatment, or treatment monitoring of cancer
  • Trainees must have had, or be enrolled in, a course in cancer biology
  • Trainees must have had, or be enrolled in, a course in research ethics training
  • Trainees must participate in the annual Radiological Physics Training Grant symposium; in addition, trainees must prepare a progress report each spring.
  • Authors of papers and theses must acknowledge partial support of the training grant in their publications
  • Appointments cannot exceed 5 years for predoctoral trainees and 3 years for postdoctoral trainees. Because of previous courses taken and research work completed, most predoctoral dissertators complete their work in 2 years.
  • Postdoctoral training includes preparing a K-series or an R series NIH grant application

Acknowledgement Requirements

Each publication, press release, or other document about research supported by an NIH award must include an acknowledgment of NIH award support and a disclaimer such as:

“Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number T32CA009206. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.”

Prior to issuing a press release concerning the outcome of this research, please notify the NIH awarding IC in advance to allow for coordination.

Current Trainees and their Projects


NameAdvisorProjectDate Appointed
Dr. Jose Guerrero GonzalezDr. Andrew AlexanderMultidimensional diffusion MRI with multivariate analyses for the investigation of tissue microscopic heterogeneity in brain cancer tumors11/1/2020
Dr. Jessica HsuDr. Weibo CaiTargeted, X-ray responsive nanoparticles for improved RT planning and treatment efficacy in breast cancer8/1/2022


NameAdvisorProjectDate Appointed
Kaelyn BeckerDr. Jon EngleProduction of 43/44Sc from isotopically enriched calcium targets to achieve clinical yields and quality9/1/2021
Collin BueloDr. Diego HernandoDevelopment of a Deep Learning-based Quantitative Susceptibility Mapping Method for Liver Iron Quantification9/1/2021
Emily SheltonDr. Paul CampagnolaDeveloping a combined theoretical and experimental approach to use the SHG spatial emission pattern of SHG to investigate the collagen fibril assembly in ovarian cancer2/1/2022
Nicholas SummerfieldDr. Carri Glide-HurstImplementing cutting-edge deep learning techniques to cardiac segmentation, namely implementing a first-of-kind UNEt+TRansformer (UNETR) algorithm and applying the techniques to a cancer patient cohort 9/1/2022
Kevin TrebDr. Ke LiDevelopment of a C-arm photon counting CT prototype system for image-guided interventional treatments of liver cancer9/1/2021
Joseph WhiteheadDr. Michael SpeidelDevelopment of a low dose, motion-compensated, quantitative x-ray imaging technique to assist with standardization of clinical endpoints during hepatic embolization procedures7/1/2021
Muhsin YounisDr. Weibo CaiTo develop novel techniques/agents for imaging and therapy of cancer and other diseases8/1/2022

Past Trainees

Click here to view a full list of trainees.