Giving Together Fund (Competitive Grant Cycle)

Summer Adventures in Learning (SAIL) is sponsored by Community Foundation of Greater Birmingham. SAIL is a partnership of funders that uses a joint application process for nonprofit organizations seeking grant support to add or enhance consistent academic components to summer youth programs, with a focus on improving reading and math skills. While the Fall 2026 cycle is closed, they have ongoing programs.

Sapere Aude: DFF-Forskningsleder (Sapere Aude: DFF Research Leader) is sponsored by Independent Research Fund Denmark (Danmarks Frie Forskningsfond). The Sapere Aude: DFF Research Leader (Sapere Aude Starting Grant) aims to give talented young researchers the opportunity to develop their research ideas and build a team around them, pursuing innovative and ambitious goals.

SCH is the flagship joint NSF-NIH programme for biomedical AI, and its defining characteristic is that it is jointly written, jointly reviewed and jointly funded - proposals are assessed once by a panel drawn from both agencies rather than being shopped between them. Three NSF directorates and more than twenty NIH Institutes and Centers participate, which gives the programme unusually wide subject coverage. The purpose is to support transformative high-risk, high-reward advances in computer and information science, engineering, mathematics, statistics and behavioural or cognitive research that address pressing questions in the biomedical and public health communities. Core themes include fairness and trustworthiness in AI and machine learning applied to health, advanced analytics for biomedical and behavioural research, multimodal sensing systems for health monitoring, cyber-physical systems for health intervention automation, robotics for healthcare support, and biomedical image interpretation informed by human perception research. The requirement that most often sinks otherwise strong proposals is structural rather than scientific: a project must make fundamental scientific or engineering contributions to two or more disciplines, and must include a mandatory collaboration plan. An application that advances clinical practice by applying existing machine learning methods, without a methodological contribution back to computing, fails that test regardless of clinical merit. The programme now operates on twice-yearly target dates rather than hard deadlines, with target dates falling in early September and early February.