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Staff Scientist 1 - Section on Functional Imaging Methods (SFIM)

Department of Health and Human Services (HHS)
National Institutes of Health (NIH)
National Institute of Mental Health (NIMH)
Division of Intramural Research Programs (IRP)
Section on Functional Imaging Methods (SFIM)

Program Overview

The National Institute of Mental Health (NIMH), a significant research component of the National Institutes of Health (NIH) and the Department of Health and Human Services (DHHS) is seeking exceptional candidates for a Staff Scientist position in the Division of Intramural Research Programs (IRP), Section on Functional Imaging Methods (SFIM).

The National Institutes of Health (NIH), Division of Intramural Research Programs (DIRP), represents one of the largest concentrations of neuroimaging researchers in the world with experts in cognitive neuroscience, mental health, neurological disorders, brain imaging, machine learning, and data science. The Section on Functional Imaging Methods (SFIM) is directed by Dr. Peter A. Bandettini, and is focused on advancing functional MRI (fMRI) acquisition, experimental, and processing methods toward the goal of better understanding the human brain. Current research in SFIM includes high spatial resolution fMRI, temporal brain dynamics during the task and resting states, maximizing neural sensitivity of fMRI, simultaneous EEG-fMRI, as well as other performance and physiologic measures, and methodology pushing neuroscience applications.

Our resources include multiple 3T and 7T MRI scanners, MRI-compatible EEG, and a world-class high-performance computing cluster ( with 90,000+ computing cores. SFIM collaborates closely with other groups such as the FMRI Core Facility, The Machine Learning and Data Science and Sharing teams, and the Scientific and Statistical Computing Core. Collaborations are available with groups performing research on clinical populations suffering from neurologic, psychiatric, and developmental disorders.

Position Overview

The Staff Scientist’s primary responsibilities include creating, modifying, reviewing, documenting, and providing technical expertise for programs, scripts, and pipelines to meet the scientific programming needs of the SFIM and support compliance with our Data and Software Policy ( ). Ultimately, the goal of this policy is to ensure that methodological innovations that come from our research will be broadly accessible and useful. Successful candidates are expected to collaborate with scientists across the NIMH, as well as with other scientific programmers in the IRP including those in the Scientific and Statistical Computing Core (SSCC), the Machine Learning Team (MLT), and the high-performance computing team (HPC). Responsibilities also include IT support, such as setting up and maintaining a data backup system and performing regular website maintenance. The selected candidate will have the ability to actively collaborate on research in SFIM and conduct novel work that aligns with SFIM's research mission. Fully in-person or periodic in-person visits are preferred, but remote workers will be considered.


Candidates must hold a Ph.D. or equivalent degree in Computer Science or Physics, Mathematics, Engineering or related field and significant experience in software development. 

Skills and expertise in the following areas are required:

  1. Proficiency in Python programming, including proficiency with NumPy and a familiarity with the scientific Python ecosystem (e.g., pandas, scipy, matplotlib).
  2. Proficiency with git and GitHub in collaborative programming environments.
  3. Proficient in a shell script such as bash, zsh, or tcsh.
  4. Ability to work in a highly collaborative, cross-disciplinary environment, across a variety of applications.
  5. A strong interest in the mission of the section, which is fMRI methods development

Skills and expertise in the below areas are desirable but not required:

  1. Experience programming in a scientific research setting.
  2. Experience training and mentoring in scientific programming.
  3. Scientific data visualization experience.
  4. Experience with AI/ML techniques and packages (such as scikit-learn and Tensorflow).
  5. Experience with methods development in MRI, EEG, and/or MEG.
  6. Advanced degrees (MS/PhD) or training in MRI, Psychology, Neuroscience, Statistics, or Physics. PhD required for a staff position.
  7. Systems administration experience in a Linux environment.
  8. Experience working with high performance computing resources such as NIH's biowulf systems or equivalent.
  9. Experience with psychology stimuli presentation software (E-PRIME, PsychoPy, Presentation, Psych Toolbox).
  10. Proficiency in Matlab programming.
  11. Proficiency in C or C++ programming, or a comparable low-level language.


How to Apply

The position is open to both U.S. and non-U.S. citizens. Salary will be commensurate with education and experience. Interested candidates must submit a current curriculum vitae, a statement of research background and interest in the position, and two letters of recommendation to Dr. Peter Bandettini via e-mail at and please copy Daniel Handwerker,

Applications will be accepted until June 9, 2023

HHS and NIH are equal opportunity employers

The NIH is dedicated to building a diverse community in its training and employment programs and encourages the application and nomination of qualified women, minorities, and individuals with disabilities.