Staff Scientist - Cyberinfrastructure and Artificial Intelligence Platforms Section (CAIP)

The CAIP seeks a scientist to serve as a senior scientist and a laboratory manager to coordinate the activities of the research group. The role will work closely with electronic health record data, genomic information, and AI technologies to predict the cause, severity, and outcomes of human diseases. The laboratory has a strong interest in digital platforms and data science cyberinfrastructure, so a strong working knowledge of data resources and their design is highly valued. The scientist’s primary responsibilities will be to work with the lab director, Dr. Sean Mooney, to both plan and implement laboratory research projects. This will include overseeing the work of research fellows and trainees, including postdoctoral fellows, graduate and undergraduate students. Helping lead management of the laboratory including research space and regular meetings, assist to recruit new staff and trainees, and building collaborative projects with NIH investigators and external investigators. The group provides 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 scientist will likely be experienced in biostatistical techniques as well as extensive computer science training in machine learning. 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.