Research Opportunities


To apply to for a position, please review the lab's current projects and contact:

Dr. Hadi Hosseini

The research in Dr. Hadi Hosseini’s lab crosses multiple disciplines including computational neuropsychiatry, cognitive neuroscience, multimodal neuroimaging and neurocognitive rehabilitation. The computational neuropsychiatry research mainly involves investigating alterations in the organization of connectome in health and disease (Alzheimer’s disease, ADHD, Stroke, etc.) using multimodal neuroimaging techniques combined with novel computational methods. The ultimate goal is to translate the findings from computational neuropsychiatry research toward developing personalized interventions for targeted enhancement of brain networks.

NIRS Neurofedback for Targeted Enhancement of Executive Functions in ADHD

The project involves testing a novel neurofeedback training technique – using near-infrared spectroscopy (NIRS) – for improving executive functions in children with ADHD. Getting involved in this study provides an opportunity for students to learn and assist with any of the following aspects of the study, depending on the student’s interests:

  1. Clinical/structured interviews and neuropsychological assessments (K- SADS, WASI, DKEFS, etc.)
  2. Computerized and Virtual Reality-based cognitive tests.
  3. NIRS-based neurofeedback intervention.
  4. Neuroimaging data collection, preprocessing, and analysis with specific focus on NIRS imaging (training in functional and structural MRI imaging is also available if interested).
  5. Scoring neuropsych assessments and entering/validating the scores on Redcap.
  6. Recruiting, scheduling/coordinating participants.

Time Committment: At least 6hrs/week

Influence of Long-Term, Multi-domain Cognitive Training on Structural and Functional Brain Networks in Mild Cognitive Impairment

This four-year project is a longitudinal study funded by National Institute of Aging (NIA) focusing on understanding the potential effects of multi-domain cognitive intervention on the organization of brain networks in older adults with and without mild cognitive impairment (MCI) using functional and structural MRI.

Getting involved in this project provides an opportunity for students to learn and assist with various aspects of the study (see below), depending on the student’s interests:

  1. Clinical/structured interviews (e.g. CDR, MINI), neuropsychological assessments, NIH Toolbox assessments, and computerized cognitive tests.
  2. Scoring neuropsych assessments and entering/validating the scores on Redcap.
  3. Neuroimaging data collection including training on running MRI scanner and collecting structural and functional brain imaging data.
  4. Preprocessing and analysis of structural and functional MRI data.

Time Committment: At least 6hrs/week

Neuroimaging Research Assistant Opening

A full-time Neuroimaging Research Assistant position is available in C-BRAIN Lab in the Division of Interdisciplinary Brain Sciences Research at Stanford University.
The position involves leading/assisting with various aspects of multimodal neuroimaging studies in human including neuroimaging data collection, preprocessing and analysis as well as taking part in manuscript preparation. The focus of neuroimaging studies in C-BRAIN Lab is on investigating alterations in the organization of human connectome in health and disease (Alzheimer’s disease, ADHD, etc.) using state of the art neuroimaging techniques (qMRI, NODDI, DWI, fMRI, fNIRS) and novel computational methods (network and multivariate pattern analyses). The lab also utilizes advanced technologies such as Virtual Reality, wearable brain imaging, physiological and behavioral tracing to build a more detailed profile of brain-behavior relationship in real-life settings. We also develop and test personalized interventions that integrate computerized cognitive rehabilitation and real-time functional brain imaging tailored toward targeted rehabilitation of the affected brain networks in patients with neurocognitive disorders.

To apply: Applicants are invited to send their resume and a cover letter (optional) to Dr. Hadi Hosseini at


  1. Bachelors in Neuroscience, Psychology, Computer Science, Statistics, Physics, Engineering, or a related field.
  2. Experience with programming in MATLAB, Python, R and/or other related computing languages.
  3. Previous experience with human subject (behavioral/neuroimaging) research.
  4. Strong analytical skills.
  5. Strong interpersonal and organizational skills.
  6. Experience with multimodal neuroimaging (fMRI, fNIRS, DWI) and related analysis packages (FSL, SPM, AFNI, HOMER, NIRS Toolbox, AnalyzIR, etc.).
  7. Strong written communication skills.

For summer/fall undergraduate internship opportunities, please view our lab's current projects and email

We are always looking for talented PhD students to rotate in the lab. Please email regarding our lab's current projects.

Postdoctoral Position in Computational Neuroimaging (fNIRS and MRI) and Multimodal Data Integration at Stanford University

A postdoctoral position is available in the C-BRAIN Lab in the Department of Psychiatry at Stanford University focusing on advanced data driven approaches for integrating multi- modal, multi-session data including neuroimaging (wearable fNIRS and MRI), behavioral, endo-immune, genetics, and VR measurements to decode heterogeneity in neural and treatment response across mental illnesses. We are specifically looking for candidates with experience in fNIRS data collection and analysis, advanced multimodal data analysis and/or computational modeling, and familiarity with MR imaging analysis.
The postdoctoral fellow will participate in collecting and analyzing multimodal neuroimaging data, mentor students and research assistants, prepare manuscripts for publication, and assist with grant applications.

Please include your CV and representative publications (up to 3) in your application.


  1. PhD (or MD) or equivalent in neuroscience, computer science, psychology, statistics, physics, engineering or a related field.
  2. Experience with fNIRS data analysis packages (HOMER, NIRS Toolbox, etc.).
  3. Experience with scripting/programming languages (Matlab, Python, R, etc.)
  4. Strong writing skills demonstrated by peer reviewed publications
  5. Strong interpersonal, organizational and mentoring skills.
  6. Familiarity with MRI data analysis (fMRI, dMRI, qMRI, etc.).
  7. Familiarity with multimodal data analyses and modeling, advanced machine learning techniques, multivariate statistics and cloud computing is a plus.