Postdoc position in neuroimaging and data science at the University of Washington
We are seeking scientists with a PhD in neuroscience, computer science, electrical engineering, statistics, psychology or related fields, and with an interest in human brain function and data science to apply for a position as a post-doc at the Institute for Learning Brain Science (I-LABS) (http://depts.washington.edu/bdelab/) and the eScience Institute (http://escience.washington.edu) at the University of Washington .
The project focuses on the development of methods for analyzing multi-modal MRI data, and the application of these methods to questions pertaining to human brain development. The long-term goals of the project are the development and maintenance of software for the analysis of large openly available datasets of human MRI, and the extraction of valuable information about the biological basis of human cognitive abilities from these data. This involves developing new algorithms for the analysis of diffusion MRI, tools for harnessing the power of cloud computing to scale these tools to large datasets and the development of new statistical and modeling techniques that are tailored to the study of brain connections. The postdoc would have the opportunity to work within a large and international open-source development community (http://dipy.org), and would be encouraged to develop a portfolio of open and reproducible science.
Suitable candidates should enjoy working in an interdisciplinary and collaborative environment, as the position sits at the intersection of the missions of eScience and I-LABS. There is one year of guaranteed funding for the position, and the opportunity to apply for extraordinary postdoctoral fellowships funded by the Washington Research Foundation, the Gordon Betty Moore Foundation and the Alfred P. Sloan Foundation (deadline: July 15th), available through the University of Washington Institute for Neuroengineering and the eScience Institute:
The University of Washington is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, protected veteran or disabled status, or genetic information.