Research Fellow - Cyberinfrastructure and Artificial Intelligence Platforms Section

The CAIP seeks a fellow to work closely with electronic health record data, genomic information, and AI technologies to predict the cause, severity, and outcomes of human diseases. The Research Fellow’s primary responsibilities will be to provide computational expertise in machine learning and biomedical informatics to a portfolio of research projects generally focused on solving challenges in human genetic disease diagnosis and treatment. Use of EHR Common Data Models, such as OMOP, molecular biological data such as protein structures, genome sequences, and curated information on human genetic disease. Techniques to be employed include machine learning approaches, generation of synthetic datasets (using generative adversarial networks and related methods), and computational workflows in the cloud. The Research fellow will likely be experienced in biostatistical techniques as well as extensive computer science training in machine learning. Duties expected will include building and maintaining collaborations with investigators and in helping coordinate consortia of investigators working together to solve difficult and important biomedical problems. The fellow will also be expected to mentor other laboratory staff and trainees.

Candidates must have a M.D. or Ph.D. in a biological field and must have a minimum of five years' experience in computational genomics or similar experience.