Hi Dipy community! Our group is looking to hire a postdoctoral fellow to work with us on diffusion imaging. Specifically we’re planning on expanding QSIPrep’s reconstruction workflows to use Dipy, MRtrix3 and DSI Studio’s group analysis tools, with application to large developmental datasets. The job listing is below, please contact us if you have any questions and feel free to share the listing with anyone who might be looking for a postdoc job. Description Ted Satterthwaite, Matt Cieslak, and the Penn Lifespan Informatics and Neuroimaging Center (PennLINC, www.pennlinc.io<http://www.pennlinc.io/>) is seeking a post-doctoral fellow to develop advanced methods for diffusion-weighted imaging, with applications to studies of the developing brain. Specifically, the fellow will build on the success of QSIPrep (qsiprep.readthedocs.io) expand the repertoire of advanced methods included in this highly reproducible and scalable framework; further integration with the Dipy ecosystem is of particular importance. These methods would then be applied to large-scale studies of brain development including the Philadelphia Neurodevelopmental Cohort (n>1,600), the Healthy Brain Network (n >2,500), and ABCD (n>11,000) to understand both normal white matter development and how abnormalities underlie neuropsychiatric syndromes. As such, the position will involve working as part of a highly interdisciplinary research team, with particular emphasis on collaborative work with leaders including Matthew Cieslak (creator of QSIPrep), Elef Garyfallidis (Indiana U; creator of Dipy), Ariel Rokum (UWash; neuroinformatics), Damien Fair (UMinn; ABCD imaging), Danielle Bassett (network science), Taki Shinohara (imaging statistics), and Mike Milham (Child Mind Institute; PI of HBN). To work effectively in this highly collaborative environment, the applicant must have superior communication, language, and writing skills. Salary is quite flexible and based upon experience; position is contingent upon funding. Applicants should contact Ted Satterthwaite (sattertt at upenn dot edu). Requirements The applicant must have completed their Ph.D. in, engineering, computer science or computational neuroscience (preferred), psychology, or statistics with an established record of high productivity. Expertise in Python, R, and neuroimaging software (e.g., ANTs, MRtrix3, FSL diffusion tools) is required; specific experience with diffusion imaging, Dipy, NiPype, and Docker is highly desirable. • Location: Philadelphia, Pennsylvania, United States • Position Title: Post-doctoral fellow: Diffusion Imaging • Company Name: University of Pennsylvania • Job Function: Engineering • Job Type: Full-Time • Job Duration: 1-2 Years • Min Education: Ph.D. • Min Experience: 3-5 Years • Required Travel: 0-10%