Postdoctoral fellowship in the Scientific and Statistical Computing Core (SSCC), within the National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Bethesda, MD, USA.
The NIMH invites applications for a postdoctoral fellow position in the SSCC, led by Dr. Paul A. Taylor.
Our Core works on methods development, collaborative applications and education within the field of FMRI/MRI/neuroimaging. Current members have strong scientific and computational backgrounds, with an emphasis on teamwork and community-oriented projects. Our Core creates new mathematical, statistical and data visualization tools, contributing to the widely used, open source AFNI software package. We partner with investigators at NIMH, NIH and globally on an extensive range of FMRI/MRI/neuroimaging projects, particularly around brain disorders and mental health research. We also have a strong focus on teaching and training, through multi-day "Bootcamps," online Message Board discussions, mentorship, and frequent consultations with practitioners.
NIMH and NIH campus are highly collaborative environments. NIMH is the largest funder of research on mental disorders in the world, and its mission is to transform the understanding and treatment of mental illnesses through basic and clinical research, paving the way for prevention, recovery, and cure. Our Core collaborates with a large number of neighboring groups on campus that have extensive expertise on MRI, brain disorders and neurological applications. Additionally, we have access to several exceptional resources, including the powerful "Biowulf" High Performance Computing cluster and several MRI scanners at various field strengths.
We are looking for a postdoctoral fellow to join our Core who has strong quantitative skills (background in STEM, computing, statistics, etc.) and who is interested in methods development, practical data analysis, creativity, and teamwork. Primary areas of interest within the group include FMRI processing, quality control, data visualization, statistical methods, applications of machine learning, computing infrastructure, algorithmic development, and multimodal applications. This position offers both focused project development and the opportunity to participate in other ongoing projects that may be of interest.
Candidates should have an interest in problem solving, both independently and collaboratively. Being able to work well with others is a key attribute. Much of our current work uses Python and C programming, with R and shell scripting also notably used. Background experience with FMRI, MRI or some other neuroimaging modality is desirable but not required. Additionally, a strong background in an area of software development, data analysis, machine learning methods, and/or statistics would be beneficial.
The earliest start date is mid-September, with some flexibility. NIH Campus is located in Bethesda, MD, just outside of Washington, DC. The area offers a rich educational, historical and cultural landscape.
The salary range is listed on the NIH Training website, along with additional eligibility criteria and program information. Interested candidates should send the following to Paul Taylor, PhD (paul.taylor _at_ nih.gov): a short cover letter expressing interest and relevant background (not longer than one page), a curriculum vitae and 2-3 reference letters (provided directly or separately from referees). The National Institutes of Health is an equal opportunity employer.