National Center for Complementary and Integrative Health (NCCIH) National Institutes of Health (NIH) Department of Health and Human Services (DHHS)

National Center for Complementary and Integrative Health (NCCIH)
National Institutes of Health (NIH)
Department of Health and Human Services (DHHS)

The National Center for Complementary and Integrative Health (NCCIH) Laboratory of Clinical Investigation invites applications for a staff scientist focused on neuroimaging methods and analysis, with a particular focus on fMRI.  The successful candidate will work jointly with the Section on Affective Neuroscience and Pain (Principal Investigator: Lauren Atlas) and the Pain and Integrative Neuroscience Branch (Prinicipal Investigator: Catherine Bushnell) and have access to cutting-edge neuroimaging facilities at NIH, located in Bethesda, Maryland. The scientist will be part of a newly established and growing research program focused on identifying the neural and psychological mechanisms of pain processing and modulation in health and disease.  

The successful candidate will work closely with Principal Investigators (PIs) and fellows to advance the neuroimaging program through data analysis and mentorship of trainees. Ongoing projects examine how psychological factors influence pain and related responses in healthy volunteers and patients, and integrate fMRI, psychophysiological, and TMS methodologies. In addition to supporting lab members and ongoing studies, the staff scientist will also have the opportunity to develop and lead independent projects in collaboration with the PI.  We seek an enthusiastic scientist who will focus on implementing techniques such as machine learning, connectivity, and graph theoretical approaches; developing new techniques; and training others on both standard and novel neuroimaging analyses.

The NCCIH Intramural Program is located on the NIH Bethesda campus within one of the most active neuroscience communities in the world ( The position offers the opportunity to work alongside some of the world’s foremost fMRI experts, and to take part in regular campus-wide seminars and workshops, including regular meetings on machine learning, fMRI methods, and pain neuroscience. The NIH Clinical Center offers exceptional multidisciplinary research facilities including structural and functional MRI, MEG, PET, and TMS. NCCIH labs are fully funded with dedicated weekly scan time on 3T and 7T scanners and multiple options for high-performance computing.  

QUALIFICATIONS/ELIGIBILITY: The candidate should have a strong background in neuroscience, statistics, computer science, psychology, or a related field and must have received a Ph.D. by the time of appointment. The candidate must possess expertise in (1) analysis of fMRI data using statistical parametric mapping packages (SPM, AFNI, etc.); (2) statistics and quantitative approaches (e.g., machine learning, computational modeling); and (3) computer programming (Matlab, C, and Python). The successful candidate should have a record of expertise in analyzing neuroimaging data.  Due to the critical interactive nature of this position, excellent teamwork and communication skills are required, and evidence of success in training others (e.g., through mentorship, workshops, and teaching) is desired. Highly competitive candidates will also possess expertise with cluster computing and Linux servers.

Salary is commensurate with research experience and accomplishments.  A full package of benefits (including retirement, health, life, and long-term care insurance, Thrift Savings Plan participation, etc.) is available.

HOW TO APPLY: Applicants must submit a current CV, a statement of research interests and qualifications for the position, and the names and contact information of three references to Lauren Atlas (

Employer Name:                   NCCIH, NIH
Position Location:                 Bethesda, MD
Application Deadline:           Until the position is filled

DHHS/NIH/NCCIH is an Equal Opportunity Employer dedicated to building a diverse community in its training and employment programs.