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Rotations for Graduate Students

I am a member of both the UPenn Neuroscience Graduate Group and also the Bioengineering Graduate Group. Contact Ted (sattertt at upenn dot edu) to set up a lab rotation.

Post-Doctoral Fellow: Neuroinformatics and Machine Learning of Brain Development

We are seeking to recruit a post-doctoral fellow focused on neuroinformatics. Anticipated research focus for this position would be to lead a major multi-site effort to aggregate, process, harmonize, curate, and publicly release major large-scale neuroimaging studies of brain development (anticipated n>10,000). Specifically, the fellow will be expected to create robust, reproducible, and scalable pipelines for the analysis of both structural and functional imaging data. Furthermore, the fellow will use sophisticated multivariate analytics to understand how abnormal patterns of brain development associate with and predict 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 (imaging informatics), Christos Davatzikos (multivariate pattern analysis), Danielle Bassett (network theory), Taki Shinohara (imaging statistics), and Mike Milham (Child Mind Institute; brain development and open science). To work effectively in this highly collaborative environment, the applicant must have superior communication, language, and writing skills. The applicant must have completed their Ph.D. in, engineering or computational neuroscience (preferred), psychology, or statistics with an established record of high productivity. Expertise in Python, R, and neuroimaging software (e.g., ANTs, FSL, AFNI, FreeSurfer) is required; experience with NiPype and Docker is highly desirable. Salary is quite flexible and based upon experience; position is contingent upon funding. Applicants should contact Ted (sattertt at upenn dot edu).

Post-Doctoral Fellow: Diffusion Imaging and Brain Development

Ted Satterthwaite and the Penn Lifespan Informatics and Neuroimaging Center (PennLINC, www.pennlinc.io) is seeking to recruit 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) and to expand the repertoire of advanced methods included in this highly reproducible and scalable framework; further integration of 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. 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. Salary is quite flexible and based upon experience; position is contingent upon funding. Applicants should contact Ted Satterthwaite (sattertt at upenn dot edu).