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 email their CV and cover letter to Ted Satterthwaite (firstname.lastname@example.org) and Matthew Cieslak (Matthew.Cieslak@pennmedicine.upenn.edu).
I am seeking to recruit a Senior Research Scientist to lead the analytic efforts of a multi-institution initiative in developmental data science. This initiative will create a large-scale public resource for developmental human neuroscience. In collaboration with Mike Milham at the Child Mind Institute, we will aggregate, process, harmonize, and publicly share >10,000 structural and functional images for youth ages 5-22. Using this massive data resource and advanced tools from network science and machine learning, we will identify normative patterns of brain network development, and identify how abnormal network development is associated with specific dimensions of psychopathology. This position will involve working as part of a highly-interdisciplinary research team that includes experts in diverse fields such as network science (Danielle Bassett), multivariate pattern analysis (Christos Davatzikos), and imaging statistics (Taki Shinohara). 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 neuroscience, engineering, psychology, or statistics with an established record of high productivity; prior post-doctoral training is highly desirable. Expertise in using neuroimaging software (e.g., FSL, ANTs, AFNI), statistical packages (e.g., R), and scripting languages (e.g., nipype, python, bash) is required. Highly competitive salary is flexible and based upon experience.
We are seeking to recruit a neuroimaging data analyst. Data analysts play a central role on large-scale projects that seek to understand brain development and the biological basis of mental illness. Within these projects, they work in a team environment with a diverse, multi-disciplinary group of faculty and trainees from psychiatry, psychology engineering, statistics, and computer science. Primary responsibilities include management, processing, and analysis of high-dimensional imaging data. Additional responsibilities will be assigned based on the successful candidate's skills and interests. All analysts additionally lead independent projects (i.e., meta-analyses of neuroimaging studies) where they write first-author manuscripts. Applicants should have a Bachelor's or Master’s degree in Engineering, Statistics, or Computational Neuroscience, and 1-2 years of research experience. Program and data analysis skills are strongly preferred, including Python, linux/bash, and R. Experience with neuroimaging tools (SPM, AFNI, FSL) is preferred but not required. To succeed in the highly collaborative environment, excellent interpersonal and communication skills are required.
I am recruiting a neuroimaging acquisition coordinator to help investigators conduct behavioral and multi-modal neuroimaging research examining both normal and abnormal brain development. Psychiatric disorders are increasingly understood as disorders of brain development, and our research seeks to situate mental illness in a developmental context. To do this, we use advanced multi-modal MRI imaging (functional, structural, metabolic) and detailed measures of behavior using digital phenotyping via smartphones. The position will draw on a wide range of skills and provide learning opportunities in diverse areas. Responsibilities will include assisting with: recruitment and acquisition of data for behavioral and multi-modal MRI data; advanced mobile phenomics and digital phenotyping via smartphones; image analysis; maintenance of regulatory documents and correspondence. Opportunities for data analysis and writing manuscripts abound. The candidate must have a passion for science, superb interpersonal skills, and technical affinity. Preference of an educational background in Neuroscience/Psychology or Biology/Premed with plans to pursue a graduate degree in psychology, neuroscience, or medicine. An interest in working directly with children, adolescents, and young adults affected by psychiatric symptoms is essential. Knowledge of IRB and human research protection regulations is desirable. While not required, experience with the Unix/Linux operating system and the statistical package R is a major asset. Above all, the applicant should demonstrate strong motivation, empathy, and excellent organizational skills.