Machine learning researcher in the NIMH IRP

The National Institute of Mental Health (NIMH) is the lead federal agency for research on mental disorders. NIMH is one of the 27 Institutes and Centers that make up the National Institutes of Health (NIH), which is responsible for all federally funded biomedical research in US. NIH is part of the U.S. Department of Health and Human Services (HHS). The NIH is a highly rated employer at glassdoor.com with very competitive salary and benefits packages.
The Machine Learning Core (MLC) is a new group created to support the use of machine learning methods in analyzing human neuroimaging data, collected within the NIMH Intramural Research Program (IRP) or from functional and anatomic imaging databases worldwide. The MLC will both develop new methods and provide education and support to NIMH IRP researchers using machine learning approaches.
What you will do:
You and the team will be responsible for assisting NIMH IRP investigators in using machine learning methods to answer clinical and scientific questions. Key areas of work include biomarkers to help diagnose mental health and neurologic disorders, as well as the development of models of mental processes in healthy subjects. You will help devise research approaches using prediction models that combine imaging and non-imaging data, and leverage structured knowledge resources (databases, scientific literature, etc) to generate explanations and hypotheses.
You will also develop new methods to address the unique research needs in our environment. You will have the resources of the NIH HPC Cluster at your disposal as well as additional help from the AWS cloud. All tools and code will be open source and freely distributed.
The MLC will provide education and outreach to further the use of machine learning across the NIMH IRP. You will be involved in designing and teaching courses on basic methods and data analysis. You will help run data analysis clinics and consults to help identify research needs, and mentor junior researchers in joint projects.
Who you are:
We are seeking candidates with practical machine learning experience, e.g. training of classification and regression models, statistical testing of results, interpretation and visualization of key aspects of models. Beyond this, we would like knowledge of optimization and statistics, insofar as they bear on machine learning method development.
Experience working with neuroimaging data (MRI, as well as MEG/EEG) will be considered very favorably, in particular the generation of quantitative measures to use as features (e.g. activation maps, functional and structural connectivity, scalar maps, cortical structure volumes, etc.).
Finally, you should have demonstrable experience coding in languages currently used in data-intensive, scientific computing such as Python, MATLAB or R (and relevant data processing libraries).
How to apply:
Email your resume (your email can serve as a cover letter) to MLCORE-JOBSEARCH-AT-mail.nih.gov
Questions are welcome. The National Institutes of Health is an equal opportunity employer.