The National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Department of Health and Human Services (DHHS), is recruiting for a Staff Scientist/Team Leader position to direct the Scientific and Statistical Computing Core/AFNI Team (https://afni.nimh.nih.gov).The primary function of this group is to support multimodal neuroimaging research in the intramural research program (IRP) at NIH. This includes (i) applying, extending, and developing new and existing software tools and techniques to conduct pioneering analyses on a diverse array of neuroimaging modalities (e.g. MRI, DTI, fMRI, MEG, PET, and EEG), (ii) advising and training IRP researchers on neuroimaging analysis methods, and (iii) leading the future growth and development of the AFNI code base (https://github.com/afni/afni). Primary responsibilities of the Team Leader will include serving as a partner in and facilitator of neuroimaging research within the NIMH IRP; providing guidance on study design; and ensuring that appropriate standards of quality, rigor, and transparency are maintained. They will also act in coordination with the leaders of the Data Science and Sharing (Data Science and Sharing Team | Center for Multimodal Neuroimaging) and Machine Learning Teams (Machine Learning Team | Center for Multimodal Neuroimaging). Finally, they will be responsible for management and supervision of approximately 9 full time staff members including software engineers, statisticians, and other biomedical science professionals. The successful candidate must be committed to scientific excellence and highly collaborative research, ensuring an immense impact on the fields of brain imaging and mental health research. Candidates must have earned a Ph.D. or M.D. and demonstrate experience as an outstanding scientist. Applicants must possess the ability to analyze, prioritize, and delegate resources while managing multiple projects. Expertise and experience should include demonstration of positive and collegial interactions with staff at all levels and the ability to communicate and promote their research, software, and scholarly contributions. Applicants should also have knowledge and experience in software engineering, including writing, distributing, maintaining, and supporting scientific software for a large user base while adhering to community recognized standards and practices.
Please see the official posting
for more details, including instructions on how to apply.