# Research Intern Positions: Multimodal Neuroimaging of Brain Vascular Function, Neuromodulation, and Clearance Research Intern Positions: Multimodal Neuroimaging of Brain Vascular Function, Neuromodulation, and Clearance Prof. Xiaoqing Alice Zhou, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School and Massachusetts General Hospital Fall 2026 Our laboratory develops and applies advanced multimodal neuroimaging approaches to understand how neuronal activity, vascular dynamics, neuromodulatory signals, and brain fluid transport interact to support normal brain function and contribute to neurological disease. Our current research combines ultra-high-field MRI with optical imaging, fiber photometry, physiological monitoring, and computational analysis to study neurovascular regulation and brain clearance in vivo. We are particularly interested in how vascular and perivascular dynamics shape brain-wide function, how neuromodulatory systems such as acetylcholine coordinate neuronal and vascular activity, and how these mechanisms are altered in aging and neurological disease. We plan to recruit undergraduate research interns with interests in either experimental multimodal neuroimaging or computational/AI-based data analysis. **Responsibilities:** Experimental and multimodal neuroimaging: Assist with preclinical high-field MRI and multimodal experiments combining MRI with fiber photometry, physiological monitoring, optical measurements, and behavioral paradigms. Depending on experience, training, and institutional requirements, students may gain exposure to animal preparation, fiber-photometry experiments, high-field MRI acquisition, and multimodal data collection. All animal-related work will be conducted under appropriate supervision and after completion of required institutional training. Computational imaging and AI-based analysis: Process and analyze high-resolution MRI and multimodal datasets. Potential projects include vascular and perivascular-space segmentation, quantitative mapping of vascular structure and dynamics, analysis of brain-wide functional signals, multimodal time-series analysis, and development of machine-learning or deep-learning methods for image reconstruction, denoising, segmentation, and biomarker discovery. Students may work with Python, MATLAB, or other quantitative imaging tools depending on the project. Students from both tracks will contribute to a broader effort to understand how neural, vascular, and neuromodulatory processes interact across spatial scales in the living brain. Projects may also investigate how these mechanisms are altered in models of aging, neurodegenerative disease, and neuropsychiatric disorders. **Requirements and Expectations:** *Approximately 8–12 hours per week is expected, ideally scheduled as one full day or two half-days per week* to allow meaningful participation in experiments and research activities. A commitment of at least one semester is expected, and students interested in continuing for multiple semesters or developing an independent research or senior thesis project are especially encouraged to apply. Prior experience with neuroscience, MRI, programming, image processing, signal processing, machine learning, or quantitative data analysis is helpful but not required. Students with backgrounds in neuroscience, biology, biomedical engineering, computer science, physics, applied mathematics, or related fields are encouraged to apply. Prior MRI or animal-research experience is not required, and appropriate training will be provided. **Additional Information:** The laboratory is located at the Athinoula A. Martinos Center for Biomedical Imaging in Charlestown, Massachusetts. Experimental work will be conducted in person, while some computational analysis may be performed remotely when appropriate. The position is unpaid and may be eligible for research course credit, including MBB 90r, subject to program approval. Students interested in developing the work into a longer-term research project or senior thesis are especially encouraged to apply. **To Apply:** Please contact Xiaoqing Alice Zhou, PhD at with a brief description of your research interests and indicate whether you are primarily interested in the experimental or computational/AI track. Please include a CV or résumé and, if available, a brief description of relevant coursework, programming experience, or prior research experience. (posted 9/2026) See also:- [ Undergrad Research or Opportunity ](/page-type/undergrad-research-opportunity)