The USC Mark and Mary Stevens Neuroimaging and Informatics Institute and Laboratory of Neuro Imaging (INI, www.ini.usc.edu) are world leaders in the development of advanced computational and scientific approaches for the comprehensive mapping of brain structure and function. LONI’s unique multidisciplinary environment and cutting-edge resources allow for integration of clinical, psychological and genotypic information with neuroimaging phenotypes for research questions in neurology, psychiatry and developmental neurobiology.

The USC Mark and Mary Stevens Neuroimaging and Informatics Institute and Laboratory of Neuro Imaging - is recruiting a talented full-time Programmer Analyst with expertise in machine learning/ deep learning, informatics, and algorithm development to address important questions related to the environmental, psychological, and biological impacts on brain health. Primary responsibilities will include developing sophisticated algorithms to discover interpretable multi-way interactions that predict various health conditions and phenotypes from complex data types (e-health, brain imaging, biometrics, environmental). Tasks will also include development of risk stratification models to understand person-level risk and risk reduction strategies. An emphasis will be placed on the use of visualization techniques to optimize the interpretability of the predictive models. Individuals with post graduate certifications in computer science courses through Edx or another platform are also strongly encouraged to apply. Proficiency in oral and written communication is required.

Preferred Qualifications:

Master’s degree in math and computer science (or related field)2-4 years of professional experienceExperience using statistical computer languages (e.g., R, Python, etc.) and scripting to manipulate and analyze data from large datasets.Experience working with and creating hierarchical data models and architecture, and using data visualization tools (e.g., Tableau, ArcGIS).Knowledge and experience working with current modeling tools (e.g., clustering, quantile regression), machine learning algorithms (e.g., gradient boosted machines, AdaBoost, ExtraTrees, etc.), deep learning techniques (e.g., 3D CNNs), and applied statistical concepts (e.g., distributions, mixed models, random effects)Evidence of algorithm development in an open domain (e.g., GitHub).Experience using SHapley Additive exPlanations (SHAP), PDPbox, and group-based trajectory modeling (for any data type) are strongly encouraged to apply.
Minimum Education: Bachelor's degree, Combined work experience and education as equivalent Minimum Experience: 1 year, Combined education/experience as substitute for minimum experience Minimum Field of Expertise: Sound knowledge of programming and documentation procedures, programming methods, program flow charts and operator instructions. Knowledge of one or more appropriate computer languages. Develops software applications using programming languages to the given design specifications. Follows design specifications to code, test, debug, install, document, and maintain software applications. Develops new and enhanced functionality for software applications. Prepares code documentation in support of program development. Performs work of moderate complexity and handles most activities under general supervision of more experienced programming staff.