Assistant Professor of Research

The USC Institute for Neuroimaging and Informatics (INI) aims to enhance discovery through the application of imaging and other data and information technologies in the study of the brain. The Institute is dedicated to excellence in data acquisition, analysis, stewardship and computational innovation for the purpose of biomedical research.

INI is comprised of the Laboratory of Neuro Imaging (LONI), the Imaging Genetics Center (IGC) and the Center for Image Acquisition (CIA). The Laboratory of Neuro Imaging (LONI) seeks to improve understanding of the brain in health and disease. The laboratory manages considerable computational infrastructure and is dedicated to the development of scientific approaches for the comprehensive mapping of brain structure and function. The Imaging Genetics Center (IGC) is involved in studying brain imaging, genetics, and the connections between them. The Center for Image Acquisition (CIA) is home to a Siemens Magnetom Prisma, a new 3 Tesla MRI scanner and a Siemens Magnetom 7T MRI scanner, and is focused on the development and application of innovative MR image acquisition in normal and diseased subjects.

In addition to the research goals, INI trains the next generation of scientists through the Masters in Neuroimaging and Informatics program. This one-year advanced program of study will provide students with a deep understanding of the scientific and clinical underpinnings of neuroimaging science and how to leverage it in large-scale to make new and important discoveries in biomedicine.

The Institute for Neuroimaging and Informatics seeks highly-qualified applicants for the position of Assistant Professor of Research (non-tenure track), with a research focus on the large-scale analysis of human brain connectivity based on neuroimaging databases. The successful candidate is expected to develop a competitive and world-class research program developing widely-used innovative algorithms for Big Data, and would coordinate large-scale analyses of vast existing datasets on brain connectivity as part of international initiatives and multiple federally funded projects.