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 Mark and Mary Stevens Neuroimaging and Informatics Institute is recruiting a talented full-time Research Engineer to help with various projects on neurodegenerative disorders. Under the supervision of the PI, the candidate will assist with data processing, analyzing the data, applying machine learning, generative AI and ensemble integration methods to the datasets, data visualization for interpretability of the models, submit abstracts and papers to conferences and assist in preparing manuscripts.

Designs, develops, and tests materials and prototypes for research projects. Investigates the feasibility of applying specific scientific principles and concepts to potential inventions and projects. Analyzes and presents data as appropriate and makes decisions to further the goals of the experiment.

Primary responsibilities will include working with large scale databases to identify and provide trajectories of brain decline. The candidate is expected to provide thorough documentation of methods publicly on GitHub, and be comfortable training coworkers in the methodologies. Tasks also include writing conference papers and assisting in manuscript preparation. The candidate will be responsible for working within the scope of funded projects, including but not limited to brain mapping in aging and Alzheimer’s disease.

Required Qualifications:

• Master’s Degree in Electrical Engineering/Biomedical Engineering/Computer Science/Data Science and 3+ years of experience in neuroimaging.

• Strong understanding of machine learning, deep learning for biomedical imaging, computer vision, Generative AI and ensemble integration of artificial intelligence methods, statistics and image processing.

• Experience working with large-scale neuroimaging and genetics data.

• Proficiency in oral and written communication as determined by contributions to scientific conferences and related presentations.

• Supervise assigned student workers for completion of a project.

• Experience in designing, developing and maintaining pipelines/tools using machine learning and deep learning for neuroimaging applications.

• Knowledge about data visualization and various data analytics tools and libraries.

Preferred Qualifications:

• 5+ years of experience in applications of AI in neuroimaging.

• Experience in working on projects related to aging of the brain to predict the structure of the brain as a function of sociodemographic and genetic factors.

• Experience building raw or segmented MR image quality assessment tools using machine learning and deep learning.

• Experience with synthetic data generation using generative models for harmonization of imaging data from multiple sources/sites using deep generative networks.

• Knowledge about ML models for classification and regression, deep learning networks like CNN’s, RNN’s, autoencoders and generative models like GANs, diffusion models, vision transformers.

• Experience writing and distributing code in Python, R, matlab, C/C++ or similar languages.

• Experience with ML frameworks such as PyTorch, Tensorflow, Keras, etc.

• Contribution to ISBI, ISMRM, OHBM, MICCAI, SIPAIM, EMBC or other AI in medical imaging and related conferences.

The annual base salary range for this position is $89,291.89 - $99,000.00. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate’s work experience, education/training, key skills, internal peer equity, federal, state, and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.

The university is committed to maintaining a safe and secure environment for students, employees, volunteers, and visitors on our campuses and those entrusted to our care, including patients, students, and minors. To that end, the university conducts background screening, including screening for criminal convictions, on all applicants after a conditional offer of employment and as a condition of employment. Please refer to the Background Screening Policy Appendix C  for specific employment screen implications for the position you are applying for.

Minimum Education: Master's degree In Engineering Or in related field(s) Minimum Experience: 3 years Minimum Skills: Experience in a laboratory setting conducting scientific research. Excellent written and oral communication skills. Ability to communicate technical information to non-technical audiences. Preferred Education: Doctorate Preferred Experience: 5 years Preferred Skills: Proven experience achieving results in a scientific research environment. Deep knowledge base in specific field.