The Department of Learning Health Sciences (DLHS) is a first-in-the-nation basic science department focused on the sciences related to learning across multiple levels of scale (i.e. individual, group, organization, region, nation). DLHS works to improve health in systemic ways by advancing the sciences that make learning effective, routine, and efficient. Our bold research programs generate new knowledge that enhance learning at all levels; our innovative educational programs train new researchers and practitioners in the sciences of learning; our collaborative service programs enhance health professions curricula and guide health systems as they evolve to become learning health systems. More information about DLHS is available at: https://medicine.umich.edu/dlhs
DLHS is seeking a highly motivated individual to join a dynamic research group focused on text analysis and natural language processing of health data. The NIH-funded postdoctoral position involves developing and evaluating computable phenotyping algorithms to identify patients living with dementia and their caregivers. Successful candidate will be an integral part of a team consisting of researchers having clinical and informatics expertise, and work on a highly collaborative research project with multiple opportunities to interact with experts and thought leaders in Alzheimer’s disease and related dementia.
The candidate will be responsible in implementing computational methods and demo systems for cohort identification and information extraction focused on people living with dementia and their caregivers. They will design, conduct, and analyze responses to multi-institutional surveys to inform best practices in pragmatic clinical trials related to dementia. The candidate will also contribute in writing research papers and technical reports based on his/her work.
- PhD or MD
- Working knowledge of health infrastructures and healthcare setting in the United States
- Strong written and verbal communication skills to effectively communicate to an interdisciplinary audience
- Sharp attention to detail
- Willingness and ability to follow instructions and work in teams
- Prior experience working with clinical or health-related free text or in statistical machine learning and text processing.
- Prior experience in conducting surveys in multi-institutional settings
- Software development experience in high performance computing clusters