• Michael Frank is a leading computational neuroscientist who has extensive experience in bridging different levels of analysis and description in computational theory, and testing these with empirical tests in humans and in animal models. He has also used this computational approach to study how brain-behavior relationships are altered as a function of disease and treatments, helping to develop the burgeoning field of computational psychiatry and neurology.
• Stephanie Jones integrates human electrophysiological brain imaging (Magneto- and Electro-encephalography MEG/EEG) and biophysically principled computational neural models to study thalamocortical dynamics of healthy brain function and disease. She has used this integrated approach to study the cellular and circuit level dynamics underlying sensory evoked and spontaneous rhythmic activity in human MEG/EEG recordings and their modulation with perception, attention, practice, and
  healthy aging. She works closely with clinicians to develop data driven models that provide testable predictions on brain dynamics and their impact on function.
• Dr. Noah Philip uses functional neuroimaging with TMS, low-current stimulation and low intensity ultrasound in combination with network-based resting state functional connectivity, and virtual reality, to understand and treat serious psychiatric disorders, such as major depressive disorder and PTSD. Large data sets with ongoing data collection range from first-in-human studies of novel stimulation devices, rational development of individualized stimulation parameters, and multimodal imaging assessments on how trauma and negative mood states affect brain responses to stimulation.
• Thomas Serre seeks to understand the neural computations supporting visual perception. His research focuses on the development of computational models of the visual cortex, as well as the development of computer vision and machine learning methods and their application for the automated analysis of neuroscience and other biology data. 

Up to four qualifying postdoctoral scientists will receive a two-year appointment. Qualifications include: 

• PhD and/or MD degree (requirements for a doctoral degree must be completed before start of the position.)
• Research experience in a computational field such as brain science, neuroscience, cognitive science, computer science, engineering, applied mathematics, or a related discipline, applicable to computational psychiatry.
• A published record of research accomplishment.
• Applicants must be a citizen or a noncitizen national of the United States or have been lawfully admitted for permanent residence at the time of appointment, per the requirements of the NIH T32 funding mechanism.

Applicants should submit a CV, statement of research interests, up to three representative publications, and names of three references through Interfolio. Candidates should address how they would contribute to the research and/or teaching missions of our diverse and inclusive university community. 

Letters of recommendation should be requested by the applicants but should be uploaded by the recommenders confidentially to the Interfolio portal. 

Candidates are encouraged to contact individual faculty trainers in advance to explore common research interests, in which case this should be mentioned in the statement of research interests. 

Application review will begin September 1, 2026.

For more information contact Kristin Webster, TPCP T32 program manager.

TPCP includes 20 trainers from six academic departments and 9 clinical mentors from the Warren Alpert Medical School at Brown University.

See the list