Amazon Research Awards
Deadline: May 7, 2024
Amazon Research Awards (ARA) is announcing the spring 2024 call for proposals for the AI for Information Security and Sustainability research areas.
ARA provides grant recipients unrestricted funds and AWS promotional credits. Funded projects are assigned an Amazon research contact, and recipients also receive training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers.
AI for Information Security
We aim to continue advancing possible solutions for some of the most challenging problems in information security. We are seeking to fund machine learning research on the following topics in information security:
- Threat, intrusion, and anomaly detection for cloud security
- Generative AI and foundation models for information security
- Graph modeling and anomaly detection on graphs
- Learning with limited/noisy labels and weakly supervised learning
- ML for malware analysis and detection
- Finding security vulnerabilities using ML
- Causal inference for information security
- Zero/one-shot learning for information security
- Reinforcement learning for information security
- Protecting and preserving data privacy in the cloud
- Securing generative AI and foundation models
Sustainability
Amazon's Sustainability Research Awards program invites proposals for innovative projects that merge machine learning (ML) and artificial intelligence (AI) techniques with life cycle assessment (LCA) methodologies to support carbon abatement strategies. This call seeks to fund projects that address the challenges associated with generating consistent, transparent, and accurate carbon measurements.
The aim of this initiative is to significantly advance the comparability of LCAs within the manufacturing, transportation, and agriculture sectors. Central to this effort is the provision of datasets, methodologies, and tools that can effectively validate that assumptions, process flows, and emission factors are uniformly applied across assessments. This focus acknowledges the critical need for verifiable data and assumptions that underpin sustainable decision-making processes. Proposals should address challenges in creating accessible solutions that ensure LCA data can be easily scrutinized and validated by stakeholders, reinforcing trust in sustainability metrics and facilitating more informed decisions. Proposals should clearly articulate how they will deliver tangible, practical outputs such as code and data, emphasizing mechanisms for ensuring data integrity and consistency in LCA practices.
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Simons Foundation: Targeted Grants in MPS
Deadline: Rolling Application (Letter of Intent)
The Simons Foundation’s Mathematics and Physical Sciences (MPS) division invites applications for its Targeted Grants in MPS program. The program is intended to support high-risk theoretical mathematics, physics and computer science projects of exceptional promise and scientific importance on a case-by-case basis.
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