AI-Ready Data Ecosystems for Pandemic Preparedness
Institute or Center: National Institute of Allergy and Infectious Diseases (NIAID)
Project: AI-Ready Data Ecosystems for Pandemic Preparedness
- Experience in Artificial intelligence (AI) methods for knowledge discovery (unsupervised learning, deep learning, etc.)
- Expertise in AI enabling knowledge representation methods (semantic networks, knowledge graphs, etc.)
- Expertise in natural language processing/automated knowledge extraction methods preferred
- Ability to work independently and collaboratively across NIAID, NIH, and other USG agencies
- Strong communications skills for role as a technical liaison among multiple stakeholders
- Knowledge of infectious and/or immune-mediated disease biology preferred
About the position: NIAID seeks a DATA Scholar with considerable experience in AI and knowledge representation methods to design and test a prototype knowledge graph with AI-ready information about a virus selected as a prototype from one of the 20 virus families with pandemic potential. The goal of the project is to automate knowledge discovery for pandemic preparedness and will be a subproject of the NIAID Data Ecosystem. The project has two distinct steps:
- Design and develop a semantic knowledge graph about the virus by representing information from published studies and internal NIAID datasets according to the Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles and enabling the use of the information by AI for automated knowledge discovery.
- Design and develop a demonstration of applying an AI algorithm to gain semantic insights from the data.
About the work: The DATA Scholar will have an exceptional opportunity to apply creativity and technical expertise to address the significant challenge of pandemic threats. The scholar will have independence with this project and the support of a strong group of collaborators, including the NIAID Data Science Working Group and NIAID Data Ecosystem partners (Scripps Research and Seven Bridges). The scholar is expected to share this project with the research community through presentations, publication, etc. as appropriate.
Datasets involved: The scholar will use data about the selected virus, including viral genome and structure, immunology, small molecules, epidemiology and transmissibility, vaccine and therapeutics trials, obtained from various public and internal NIAID data repositories and data sources (e.g., ImmPort, BRCs, IEDP, GenBank, dbGaP, AnVIL, PDB, UniProt, clinical and epidemiological data, published literature)
Why this matters: Pandemic threats pose a major challenge to human health and society. NIAID is at the center of responding to potential threats by developing countermeasures (diagnostics, vaccines, and therapeutics) and pandemic preparedness strategies for the US Government. The use of AI and computational methods has been limited so far, but the profound impact of COVID-19 revealed the need to represent knowledge of viruses of pandemic potential in AI-accessible formats and systems. AI-accessible systems will allow researchers to better prepare for outbreaks with epidemiological data and promising countermeasures. This project explores the potential of AI and automated knowledge discovery to support pandemic preparedness efforts.
Work Location: Rockville, Maryland (remote work allowable)
Work environment: The scholar will work independently under supervision of Dr. Wilbert Van Panhuis (Director, NIAID ODSET), with mentoring and support from NIAID, NIH, and other US Government senior staff with wide-ranging scientific, technical, and administrative expertise.
To apply to this or other DATA Scholar positions, please see instructions here: datascience.nih.gov/data-scholars-2022.
This page last reviewed on April 7, 2022