Skip to main content

Transforming the understanding
and treatment of mental illnesses.

Celebrating 75 Years! Learn More >>

Job Vacancy Announcement – Staff Scientist 1 – Section on Learning and Plasticity (SLP)

Department of Health and Human Services (HHS)
National Institutes of Health (NIH)
National Institute of Mental Health (NIMH)
Division of Intramural Research Programs (IRP)
Laboratory of Brain and Cognition (LBC)
Section on Learning and Plasticity (SLP)

Program Overview

The National Institute of Mental Health (NIMH), a major 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 1 position in the Division of Intramural Research Programs (IRP), Section on Learning and Plasticity (SLP) in the Laboratory of Brain and Cognition (LBC). The aim of the SLP is to better understand how the structure, function, and selectivity of the cortex change with experience or impairment, even in adulthood. Toward this goal, there are three main avenues of research, principally using brain-imaging techniques. The first avenue concerns the nature of perceptual representations in the human brain, focusing on complex visual stimuli such as faces, bodies, scenes, and words. The second avenue explores how experience and learning change the neural and cognitive representations of sensory input. For example, what are the neural changes underlying our enormous capacity to learn to recognize new objects and to make fine-grained discriminations among those objects? The third avenue concerns how the cortex adapts following damage to the nervous system (either peripheral or central). For example, what is the impact of macular degeneration (loss of foveal vision) or amputation on cortical function, and how does that relate to conditions such as phantom limb pain (pain in the missing limb)? Elucidating the nature and extent of cortical plasticity is critical for understanding brain function throughout life.

Position Overview

The Staff Scientist’s primary responsibilities include independently conducting research related to the neuroimaging of high-level vision, memory, and learning. In addition, the individual will support and train lab members, develop analysis pipelines, establish and conduct collaborative research, attend and present at national and international meetings, and assist in writing manuscripts. The Staff Scientist will have the opportunity to integrate a wide range of behavioral and imaging technologies, including magnetoencephalography (MEG), structural and functional magnetic resonance imaging (fMRI, dMRI), eye tracking, and computational modeling (e.g., deep neural networks). They will also be expected to interface with other groups at NIH, including the fMRI facility, the MEG core, and the Machine Learning Team.


Candidates must hold a Ph.D. in neuroscience, psychology, computer science, or a related discipline. In particular, we are seeking someone with specific skills, knowledge, and experience with fMRI, MEG, or EEG. Proficiency with any major neuroimaging packages (e.g., AFNI, FSL, Freesurfer), strong programming skills (e.g., python), and experience with 7T MRI would be valuable.

How to Apply

The position is open to both U.S. and non-U.S. citizens. Applications from women, persons from underrepresented groups, and persons with disabilities are strongly encouraged. Salary will be commensurate with education and experience. The position is subject to a background check. 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. Christopher Baker via e-mail at and please cc When submitting, please put the email subject line as “Staff Scientist- SLP.”

Applications will be accepted until May 10, 2024. 


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.