Programme Coordinator

Programme Procurement Specialist

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 U.S. Embassy Kuala Lumpur Public Diplomacy Section seeks proposals that advance American leadership, prosperity, and security interests in Malaysia. This program supports initiatives that promote U.S. technological innovation and economic competitiveness, showcase American excellence in sports and education, strengthen ties with exchange program alumni, and position the United States as Malaysia's most trusted international partner.   Priority areas include: advancing U.S. leadership in artificial intelligence and emerging technologies; leveraging major sporting events to demonstrate American excellence; engaging alumni networks to amplify U.S. influence; and promoting American English language education and pathways to U.S. higher education institutions. Programs should demonstrate clear alignment with U.S. national interests, measurable outcomes, and sustainable impact beyond the grant period. Successful proposals will engage influential Malaysian stakeholders, promote American standards, and contribute to making America more prosperous and secure.

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.

Priority Region: Sub-Saharan Africa  Africa Regional Services (ARS) Paris, part of the U.S. Department of State’s Bureau of African Affairs, invites U.S. citizen speakers, artists, and athletes/coaches to submit Statements of Interest (SOIs) for inclusion on the ARS U.S. Speaker Program roster. Roster members may be selected for small program specific grants to conduct in-person and virtual outreach across sub-Saharan Africa.  The ARS Speaker Program supports U.S. foreign policy goals in Africa by strengthening security, supporting shared prosperity, and promoting American excellence. In line with the Department’s Freedom 250 initiative marking the 250th anniversary of the United States and the Decade of Sport in America programs are encouraged to:  Share the American story and 250 years of American excellence in innovation, technology, and culture; and celebrate American achievement in sports.  Lead the next era of results driven U.S.–Africa partnership.  This Annual Program Statement seeks U.S. citizen individuals with demonstrated expertise who can deliver programs in English  and  either French or Portuguese.   Priority Program Areas include security; economic prosperity, innovation, technology, and entrepreneurship; energy security, and critical minerals; and American arts, sports, and creative industries as engines of economic opportunity.  Selected individuals will be added to the ARS roster following review and interview. Being on the roster does not guarantee funding; individual grants will be made only when a specific U.S. embassy or consulate request matches a roster member’s expertise and availability. SOIs must be submitted using the dedicated form available at  https://forms.office.com/g/NyK95VxSH9 . All supporting documents (credentials/testimonials/endorsements, U.S. passport and a CV or résumé) must be emailed to  arsspeaker@state.gov . Make sure the email subject line says “SOI” with your full name. Incomplete Statements of Interest will be rejected.   

Quantum Machine Learning