Data and Partnerships Associate
Astera Institute is an active nonprofit research institute and foundation that operates in-house neuroscience-informed AI research and funds, operates, and supports open-science programs and public goods.
About Astera Institute
Astera operates three divisions: Neuro-AI, Radial life-sciences research, and its Foundation. Its AI work pursues neuroscience-informed approaches to artificial general intelligence, while its foundation and Radial activities support open scientific infrastructure, datasets, research programs, and residencies.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will oversee research data throughout its lifecycle, uphold data quality and FAIR standards, and develop scalable data infrastructure. You will guide partners and researchers on data management, maintain federal partnerships, support knowledge-graph integration, and address responsible data-sharing needs.
Requirements
- Manage data in research organizations, academic institutions, or similar environments with complex data governance
- Apply data quality principles, data governance frameworks, and metadata standards
- Understand scientific data formats, repositories, and standards
- Build partnerships with outside organizations, particularly federal-government partners
- Translate technical data requirements for researchers
- Manage multiple data projects
- Understand FAIR data standards
- Understand open science
Responsibilities
- Serve as a contact for the National Science Foundation Programmable Cloud Lab Test Bed Network partnership
- Consult partners on preparing and publishing high-quality reusable data
- Ensure partners follow data policies
- Initiate and maintain federal-government partnerships
- Maintain documentation, metadata tools, standards, and data-release practices
- Train partners and researchers on data-management practices
- Identify and address technical gaps in data infrastructure
- Integrate research data with open-science knowledge graphs
- Develop responsible data-release approaches for sensitive, private, safety-related, or dual-use research