UK Global Screen Fund (UKGSF) International Distribution Video Game Release funding

Apply for funding to run a high throughput screen (HTS) using AstraZeneca’s compound library and screening robots. There are two funding opportunities per year that are open to all targets.

The Heat Network Efficiency Scheme (HNES) provides funding to public, private and third sector applicants, to support improvements to existing district heating or communal heating projects in England and Wales that are operating sub-optimally and resulting in poor outcomes for customers and operators. Projects can apply to HNES for either revenue or capital grant funding: Revenue grants – grants to fund procurement or mobilisation of external third-party support to carry out Optimisation Studies. These studies will assess heat network projects to identify causes of sub-optimal performance and recommend costed intervention or improvement measures. Capital grants – grants to part-fund the delivery (installation) of eligible intervention/improvement measures.

Supporting UK producers to work as partners on international co-productions and help create new global projects.

Supporting UK films to reach international audiences.

Supporting the festival launch of UK films in order to enhance their promotion, reach and value internationally.

Spruce Site Assessment can help to evaluate costs involved in felling spruce in the proactive spruce removal area and identify funding available to help with the cost.

Supporting UK screen content businesses across film, TV, animation and interactive narrative video games to enhance their international activities.

The American Institute in Taiwan Public Diplomacy Section announces an open competition for one cooperative agreement to support the implementation of four Global Cooperation and Training Framework Classic workshops in Taiwan during calendar year 2027. The GCTF is a capacity building platform that brings together government officials, industry experts, academics, and civil society representatives to exchange practical experience and promote professional cooperation on emerging regional and global challenges. Workshop topics will be jointly identified by GCTF partners and may address resilience, emerging technologies, economic security, trusted supply chains, democratic governance, and other shared priorities. The selected recipient will serve as the implementation partner responsible for comprehensive operational and administrative support, including venue coordination, participant registration, international travel support, interpretation, audiovisual services, workshop materials, vendor coordination, site visits, monitoring and evaluation, and required grant reporting. Most workshops are expected to take place in Taipei, with one anticipated in southern Taiwan. AIT and GCTF partners will provide policy guidance, strategic direction, and substantive oversight. The project is intended to strengthen international cooperation, promote policy dialogue and capacity building, improve continuity across GCTF programming, and advance practical exchanges among government, industry, academia, and civil society.

This is a notice of funding opportunity (NOFO) for the BJA FY 2026 Daniel Anderl Judicial Security and Privacy Program. This opportunity supports states and units of local government, including tribal governments that perform law enforcement functions, in creating and expanding efforts to protect the safety and security of federal judges by preventing the release of covered information about at-risk individuals and their immediate family members to ensure federal judges are able to administer justice fairly without fear of personal reprisal from individuals affected by the decisions they make in the course of carrying out their public duties. Many federal judges' personal information resides in state and local government records, databases, and registries that are publicly accessible and searchable and outside federal control. Grants to state and local entities support federal-state-local partnerships to protect federal judicial officers and their families. Funds awarded under this grant program must be used exclusively for protecting federal judges and their immediate family members as defined in statute. Applicants that have existing judicial protection programs should clearly delineate how grant funds will be used solely for federal judges and describe cost allocation methodologies to ensure appropriate separation of expenses. Expenses that also benefit other judges are acceptable, provided that any costs specific to state, local, or tribal judges are separately tracked and are not charged to this grant.

The overarching goal of this notice of funding opportunity (NOFO) and its companion opportunities is to establish the Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) Program to support development of innovative, reliable, cost-effective, and sustainable multimodal AI-based clinical decision support (CDS) tools. PRIMED-AI CDS tools are based on the integration of clinical imaging with other types of multimodal health data to enhance care for patients with a wide range of health conditions. The PRIMED-AI Program seeks to catalyze the adoption of AI-based CDS tools into clinical workflows to enable novel personalized medicine strategies that address significant health challenges. The purpose of this NOFO is to solicit applications for the design, development, and preliminary validation of robust frameworks for the application of multimodal-artificial intelligence (AI) models for clinical use. Frameworks developed through these awards would populate a "playbook", defined as a collection of actionable guidelines, standardized protocols, and/or standard operating procedures (SOPs) for reliable and effective development and deployment of multimodal AI tools. It is expected that the frameworks delineated in this playbook will directly address PRIMED-AI objectives and needs, while also remaining flexible enough to enable sufficient extensibility and interoperability for use across a broad spectrum of multimodal biomedical AI applications, both internal and external to the PRIMED-AI Program.