Postdoc Fellow: Rehabilitation Medicine Department (RMD), Epidemiology and Biostatistics Section

We are seeking a post-doctoral fellow to engage in a multi-year project using natural language processing or text mining to analyze medical records and programmatic documents for the nation's largest disability programs, Social Security Disability Insurance (DI) and Supplemental Security Income (SSI), administered by the Social Security Administration (SSA). This is an unprecedented opportunity to harness unstructured information from millions of documents, use this information to improve SSA's disability adjudication process, and advance the body of medical knowledge related to disability. Our interdisciplinary program is designed to provide experiences that foster the development of skills necessary to conduct independent research and to cross-train post- doctoral fellows in disciplines that are not traditionally represented in Rehabilitation Medicine such as mathematics, statistics, economics, engineering, or computer science. Our training program is intended for students interested in population-level health services research and disability-related public health issues; however, our fellows are encouraged to become actively engaged in the rich and vibrant NIH research community. This is a fully funded multi-year post-doctoral fellowship.

Research areas: natural language processing, text mining, machine learning

Role: As a postdoctoral fellow, you will conduct research in NLP/Text Mining, develop novel algorithms, implement prototypes, present and publish your work. You will research and identify new technologies, systems or applications of relevance to SSA's and NIH's NLP vision. You will collaborate with a multi- disciplinary team of scientists on a wide range of problems. This position will bring analytical rigor and statistical methods to the challenges of improving the accuracy, efficiency, and timeliness of SSA's disability programs. 

•        PhD in computer science, computational linguistics or related field from an accredited university
•        Dissertation in natural language processing/text mining, or machine learning
•        A minimum of 18 semester hours in computer science, computational linguistics, statistics, or applied mathematics
•        Excellent quantitative and applied research skills
•        Strong oral and written communication skills
•        Ability to work effectively in a multidisciplinary team setting
•        Demonstrated proficiency in programming with a high-level programming language
•        Knowledge of state-of-the-art NLP/Text Mining methods
•        Experience applying deep learning techniques to text data

For prompt consideration email the documents listed below to Amy Yang, Management Analyst, Epidemiology and Biostatistics Section, National Institutes of Health, Mark O. Hatfield Clinical Research Center, Rehabilitation Medicine Department, Email: amy.yangnih.gov.  Please refer to this announcement as the “NIH-RMD SSA NLP post-doctoral fellowship_[LAST NAME]”.

Application materials:

•        curriculum vitae
•        a summary of past research experience
•        graduate transcript
•        a copy of one of your published papers
•        a list of at least three references

The NIH is dedicated to building a diverse community in its training and employment programs.