Positions Available

SFIM

Please contact Peter Bandettini at bandettini@nih.gov if you are potentially interested in a postdoctoral, graduate student, Summer internship, postbaccalaurate IRTA, or visiting researcher position.

Scientist / Programmer Contractor
Section on Functional Imaging Methods
National Institute of Mental Health
National Institutes of Health
Department of Health and Human Services, Bethesda, MD

The Section on Functional Imaging Methods (SFIM), a research group within The National Institute of Mental Health (NIMH) intramural program, is seeking an exceptional candidate to serve on our staff. The responsibilities include conducting independent and collaborative research, supporting and training SFIM members in their use of computational resources, helping to design and program brain activation stimuli or processing methods, as well as IT support. 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.

SFIM, directed by Dr. Peter A. Bandettini, is focused on advancing functional MRI (fMRI) acquisition, experimental, and processing methods towards the goal of better understanding human brain physiology. The section also conducts cutting-edge research on functional brain organization towards the goals of better understanding the human brain and creating brain imaging based clinical tools. Research in the SFIM currently revolves around four primary themes: high field and high resolution fMRI, dynamic connectivity assessment during rest and activation, individual assessment, and maximizing neural sensitivity of fMRI. We are currently developing novel analytic methods for naturalistic stimuli, novel real time fMRI interactive acquisition approaches, layer fMRI acquisition and analysis methods, multi-echo fMRI acquisition and analysis methods, and simultaneous EEG-fMRI.

The applicant for this position should have M.S. or Ph.D level experience in a field related to fMRI, EEG, MEG, and/or MRI, such as Psychology, Neuroscience, Engineering, Computer Science, Statistics or Physics. Preference will be given to applicants with the following:

  1. A history of methods development in MRI, EEG, and/or MEG
  2. A strong passion for developing and advancing multimodal imaging methods, and, in particular, fMRI.
  3. Strong coding proficiency. Ideally this would include Python's scientific, machine learning, and visualization tools, git, and shell scripting.
  4. Experience with scientific computing, ideally with MacOS, Linux, and working with high performance computing resources (e.g NIH Biowulf cluster or equivalent cluster)
  5. Experience with one or more of the major neuroimaging platforms (e.g. AFNI, fMRIPrep, FreeSurfer, FSL, SPM)
  6. Experience with stimuli software (E-PRIME, PsychoPy, Presentation, Psych Toolbox)

The selected candidate will help develop existing and/or new lines of research that align with the SFIM's research mission. Candidates will be encouraged to develop their own research interests. They will also help with scientific computing support to the SFIM. The balance of the research and computational support roles for this position will depend on existing skills, experience, and interests.

Among our most utilized resources are: 3T and 7T MRI scanners, cutting edge pulse sequences for MRI and fMRI, a world-class high-performance computing cluster with 99,000+ computing nodes and over 30 petabytes of storage, state-of-the art neuroimaging and neuromodulation facilities, MRI-compatible 256-channel EEG, MEG, tDCS/tACS, TMS, as well as behavioral testing facilities. 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.

Applicants should send a curriculum vitae and a cover letter/email to Peter A. Bandettini, Ph.D. (bandettini@nih.gov, Building 10, Room 1D80, 10 Center Drive, Bethesda, MD 20892-1148, 301-402-1333 TTY: MD Relay Operator at 1-800-735-2258). The National Institutes of Health and Kelly Contractor Service are equal opportunity employers. Salary for this position is defined by type of training and years of experience.

 

Postdoctoral Positions
Section on Functional Imaging Methods
National Institute of Mental Health, National Institutes of Health
Department of Health and Human Services
Bethesda, MD, USA

The National Institute of Mental Health (NIMH) invites applications for postdoctoral positions in the Section on Functional Imaging Methods (SFIM), directed by Dr. Peter A. Bandettini. Research is focused on advancing functional MRI (fMRI) acquisition and processing methods towards the goal of better understanding human brain dynamics and physiology, as well as to determine fMRI and MRI correlates to behavior and disease. Current areas of research in the SFIM include: use of naturalistic stimuli for subject phenotyping, development of layer fMRI acquisition and analysis methods, characterization and interpretation of static and dynamic aspects of functional connectivity, development of multi-echo fMRI analytical methods, simultaneous EEG-fMRI, neuromodulation, and examination of the limits of what fMRI can reliably measure.

The SFIM is a team of physicists, psychologists, engineers, neuroscientists, and computer scientists committed to advancing the field of fMRI and the role it plays in improving our understanding of brain function. Our group has access to state-of-the art neuroimaging and neuromodulation facilities, including 7T and 3T MRI scanners, MRI-compatible 256-channel EEG, MEG, tDCS/tACS, TMS, as well as behavioral testing facilities. We collaborate with groups performing research on clinical populations suffering from neurologic, psychiatric, and developmental disorders. We also work closely with the functional MRI Core Facility, the NIMH Machine Learning Team, the Data Science and Sharing Team, and the Scientific and Statistical Computing Core Facility.

The applicant for this position should have a Ph.D. (or equivalent) in a specialty related to fMRI, EEG, MEG, and/or MRI and a strong passion for developing and advancing fMRI methods. The applicant must be able to work independently, highly skilled in functional neuroimaging and data analytics, as well as be excited to learn novel ways to explore and interpret neuroimaging data. The applicant is expected to have deep expertise in some particular aspect of neuroscience, imaging, or data science, and the desire to work collaboratively to advance the research goals of the section. Salary for this position is defined by type of training and years of experience

(https://www.training.nih.gov/postdoctoral_irta_stipend_ranges)

The NIH is among the largest and best communities of MRI researchers in the world, with opportunities to collaborate with leaders in the field of fMRI, DTI, susceptibility contrast, parallel imaging, and molecular imaging, among other MRI-based specialties.

Applicants should send a curriculum vitae, and three letters of recommendation to Peter A. Bandettini, Ph.D. Building 10, Room 1D80, 10 Center Drive, Bethesda, MD 20892-1148, 301-402-1333, bandettini@nih.gov, TTY: MD Relay Operator at 1-800-735-2258. The National Institutes of Health is an equal opportunity employer.

 

Joint Columbia/NIMH postdoctoral position

We are seeking a post-doctoral fellow (or equivalent) to be co-supervised by Elizabeth Hillman at Columbia University’s Zuckerman Institute and Peter Bandettini at the National Institute of Mental Health Intramural Research Program. This position requires expertise in dynamic data analysis and a strong interest in exploring the neural basis of functional magnetic resonance imaging.  fMRI data acquired in humans will be compared to mouse wide-field optical imaging of neural activity and hemodynamics to test and inform improvements in fMRI data analysis, particularly in relation to resting state functional connectivity mapping methods. The individual may have a computational, neuroimaging or engineering background, with a preference for prior experience in fMRI analysis. This position could be a postdoctoral fellowship or for someone without a doctorate who has relevant skills and experience.

The position could be geographically located in either New York or the Washington DC area.

The Hillman lab (https://zuckermaninstitute.columbia.edu/elizabeth-hillman-phd ) within Columbia’s new Zuckerman Mind Brain Behavior Institute is an energetic, diverse group with broad interests spanning imaging technology development and its application to answering novel questions relating to real-time brain activity and its relation to behavior across the scales and species. Our neurovascular coupling work seeks to better inform the interpretation of human fMRI data in health and disease through elucidation of the mechanistic underpinnings of the BOLD signal.

Dr. Bandettini’s Section on Functional Imaging Methods at the National Institutes of Health (https://fim.nimh.nih.gov/ ) is a team of physicists, psychologists, engineers, neuroscientists, and computer scientists committed to advancing the field of fMRI by developing of improved fMRI data acquisition and processing methodology, shedding light on the relationship between neuronal activity and hemodynamic changes, characterizing the sources of artifact and useful information in the signal, and bridging the gap between basic development and research and clinical applications.

Interested applicants should submit their Curriculum Vitae, cover letter and list of references to: Elizabeth.hillman@columbia.edu, bandettp@mail.nih.gov, and Dan.Handwerker@nih.gov

Women and minorities are strongly encouraged to apply.


 

Machine Learning Group

This facility develops novel ways to use machine learning methods for neuroimaging data and to help intramural NIH researchers apply machine learning methods to their data.
https://cmn.nimh.nih.gov/mlt
Email MLCORE-JOBSEARCH@mail.nih.gov for inquiries.



Data Science and Data Sharing Group

This facility develops procedures and infrastructure to facilitate sharing and analysis of data from the thousands of volunteers each year who participate in intramural neuroimaging studies.
https://cmn.nimh.nih.gov/dsst
Email DATASCI-JOBSEARCH@mail.nih.gov for inquiries

 

 

 

  • National Institute of Health
  • National Institute of Mental Health
  • Department of Health and Human Services