Senior Research Scientist

Location
Pennsylvania, United States
Posted
23 Apr 2019
End of advertisement period
23 Jun 2019
Ref
40-31765
Contract Type
Fixed Term
Hours
Full Time

The University of Pennsylvania, the largest private employer in Philadelphia, is a world-renowned leader in education, research, and innovation. This historic, Ivy League school consistently ranks among the top 10 universities in the annual U.S. News & World Report survey. Penn has 12 highly-regarded schools that provide opportunities for undergraduate, graduate and continuing education, all influenced by Penn’s distinctive interdisciplinary approach to scholarship and learning.

Penn offers a unique working environment within the city of Philadelphia. The University is situated on a beautiful urban campus, with easy access to a range of educational, cultural, and recreational activities. With its historical significance and landmarks, lively cultural offerings, and wide variety of atmospheres, Philadelphia is the perfect place to call home for work and play.

The University offers a competitive benefits package that includes excellent healthcare and tuition benefits for employees and their families, generous retirement benefits, a wide variety of professional development opportunities, supportive work and family benefits, a wealth of health and wellness programs and resources, and much more.

The Perelman School of Medicine at the University of Pennsylvania is the oldest and one of the finest medical schools in the United States. Penn is rich in tradition and heritage and at the same time consistently at the forefront of new developments and innovations in medical education and research. Since its founding in 1765 the School has been a strong presence in the community and prides itself on educating the leaders of tomorrow in patient care, biomedical research, and medical education. http://www.med.upenn.edu/

Ted Satterthwaite and the Lifespan Brain Institute are 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 collaborators at Child Mind Institute (lead by Mike Milham) we will aggregate, process, harmonize, and publicly share >10,000 structural and functional images for youth ages 5-22. Using this massive data resource, we will seek to develop normative patterns of brain network development, and identify how abnormal network development is associated with specific patterns 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 S. 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; post-doctoral training is desirable. Expertise in using neuroimaging software (e.g., FSL, ANTs, AFNI), pipelining software (nipype), statistical packages (e.g., R), and scripting languages (e.g., python, bash) are required. Salary flexible based upon experience.

Highly advanced professional discipline. M.D., Ph. D., Law degree or equivalent doctoral degree and 5 years to 7 years of experience or equivalent combination of education and experience is required. Experience must include processing and analysis of neuroimaging data. The ideal candidate will have demonstrated excellent qualifications in quantitative methodologies, especially neuroimaging data analysis .

Penn adheres to a policy that prohibits discrimination on the basis of race, color, sex, sexual orientation, gender identity, religion, creed, national or ethnic origin, citizenship status, age, disability, veteran status, or any other legally protected class.