These will include, but not be limited to, advances in core Jupyter components for collaboration and data sharing across deployments in separate hosting environments (ranging from local clusters and HPC facilities to the cloud), integration of AI agents and tools into the research workflow, sharing of intermediate results, code and pre-publication outputs with fine-grained access control, and fluid integration of these Jupyter deployments alongside existing research tools and environments that are independent of Jupyter. Please submit a cover letter including 1) links to up to 3 publicly available GitHub repositories that highlight engagement in issues, pull requests, community discussions (or equivalent conversations on alternative git forge platforms), 2) links to a research output (eg: research paper, analysis code, educational resources, etc) showcasing your expertise in the biomedical field, and 3) a description of a previous role (paid or volunteer) where you have identified and delivered outcomes in the presence of uncertainty.