Amazon Research Awards AI for Information Security Call for Proposals Spring 2026 is sponsored by Amazon. The Amazon Research Awards (ARA) AI for Information Security Spring 2026 call funds academic research at the intersection of artificial intelligence and cybersecurity.

AI for Information Security call for proposals - Spring 2026 - Amazon Science Information and knowledge management Operations research and optimization Security, privacy, and abuse prevention Our scientific contributions Research from our scientists and collaborators. Our experts present and discuss cutting-edge research at scientific meetings globally.

Information and knowledge management Operations research and optimization Security, privacy, and abuse prevention Our scientific contributions Research from our scientists and collaborators. Our experts present and discuss cutting-edge research at scientific meetings globally. The latest from Amazon researchers Technical deep-dives and perspectives from our scientists.

Research milestones and recent achievements. The latest from Amazon researchers Technical deep-dives and perspectives from our scientists. Research milestones and recent achievements.

Carnegie Mellon University Tennessee State University University of California, Los Angeles University of Illinois Urbana-Champaign University of Southern California University of Texas at Austin Carnegie Mellon University Tennessee State University University of California, Los Angeles University of Illinois Urbana-Champaign University of Southern California University of Texas at Austin Meet the team building useful AI agents.

Try Amazon’s frontier foundation models. Meet the team building useful AI agents. Try Amazon’s frontier foundation models.

Faculty research opportunities on industry-scale technical challenges. Postdoctoral Science Program Early-career research opportunities alongside experienced industry scientists. Faculty research opportunities on industry-scale technical challenges.

Postdoctoral Science Program Early-career research opportunities alongside experienced industry scientists. AI for Information Security call for proposals - Spring 2026 Advancing possible solutions for some of the most challenging problems in information security By Amazon Research Awards team At Amazon, we aim to continue advancing possible solutions for some of the most challenging problems in information security.

We are seeking to fund AI research on the following topics in information security: Trustworthy and reliable agentic AI for security operations, including methodologies for evaluating AI agents in security use cases AI agent access governance: policy verification, guardrails, and conditionally scoped authentication and authorization Threat, intrusion, and anomaly detection in agentic AI systems and cloud environments AI-powered incident response and red-teaming Vulnerability detection and remediation using agentic AI Building and optimizing foundation models through pre-training, post-training, fine-tuning, and other techniques to improve performance on security tasks Security of agentic AI systems, including securing toolchains, securing frameworks, solutions for confused deputy in delegated agent behaviors, and so forth Securing generative AI and foundation models, including securing training data content, anonymization, semantic differential privacy, preventing data leakage from trained models, and so forth Reinforcement learning for information security Scalable and efficient graph modeling and anomaly detection on graphs Learning with limited/noisy labels and weakly supervised learning AI for malware analysis and detection, with a focus on cloud environments or devices AI-assisted secure code generation and security enhancement of existing codebases Generative AI for cloud infrastructure compliance Submission period: March 25, 2026 — May 13, 2026 (11:59PM Pacific Time) Decision letters will be sent out in August 2026 Selected Principal Investigators (PIs) may receive the following: Unrestricted funds, no more than $80,000 USD on average AWS Promotional Credits , no more than $40,000 USD on average Training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers Awards are structured as one-time unrestricted gifts.

The budget should include a list of expected costs specified in USD, and should not include administrative overhead costs. The final award amount will be determined by the awards panel. Please refer to the ARA program rules on the rules and eligibility page .

Proposals should be prepared according to the proposal template and are encouraged to be a maximum of 3 pages, not including Appendices. AI for Information Security will make the funding decisions based on the potential impact to the research community and the quality of the scientific content.

Expectations from recipients Amazon Research Awards team Sr. Research Scientist, Pricing Science Amazon's Worldwide Pricing & Promotions organization is seeking a talented, hands-on Research Scientist to join the Pricing and Promotion Optimization Science (P2OS) team — the optimization "application layer" within Amazon's Pricing Sciences organization.

Amazon adjusts prices on hundreds of millions of products daily across a global marketplace; P2OS is the team that makes those prices optimal. P2OS is a small, specialized unit with an outsized charter: develop and maintain the models that determine optimal prices and promotions across Amazon's catalog and merchant programs.

We own the full optimization stack — from price prediction to promotion targeting to competitiveness guardrails — and we measure success in terms of accretive Gross Contribution and Customer Pricing Perception (GCCP).

Our work spans Retail Core, Amazon Business, Fresh, Grocery, and international marketplaces, and we are continually investing in more extensible, generalizable science foundations to keep pace with a growing and evolving business.

We are looking for an innovative, organized, and customer-focused scientist with exceptional machine learning and predictive modeling skills, causal and experimental evaluation experience, and the entrepreneurial spirit to apply state-of-the-art methods to some of the most impactful pricing problems in e-commerce.

You should be comfortable with ambiguity, motivated by measurable business impact, and excited by the opportunity to work at Amazon-scale. Key job responsibilities * Innovate and build. Design, develop, and deploy machine learning models that set optimal prices and promotions across Amazon's global catalog.

Own models end-to-end — from problem formulation and data analysis through offline evaluation, A/B testing, and production launch. * Build a generalizable science foundation. Develop models and evaluation frameworks designed to scale across merchant programs, product categories, and marketplaces — enabling cross-learning and reducing the time and cost of applying science to new business contexts.

* Build and evolve optimization systems. Design and improve optimization systems — including reinforcement learning and multi-objective optimization approaches — that automate price and promotion decisions at scale across millions of products. * Apply generative AI and foundation models.

Identify and pursue opportunities to leverage large language models, embeddings, and generative AI techniques in pricing science — from enriching product representations and extracting competitive signals from unstructured data, to building more capable and explainable pricing systems. * Experiment rigorously. Design and execute A/B tests and causal inference studies to measure the business and customer impact of pricing model changes.

Translate findings into production-ready science improvements. * Stay at the frontier. Establish mechanisms to track the latest advances in reinforcement learning, causal ML, multi-objective optimization, generative AI, and demand modeling — and identify opportunities to apply them to Pricing & Promotions business problems.

* See the big picture. Contribute to the long-term scientific vision for how Amazon sets competitive, perception-preserving prices — balancing profitability, customer trust, and marketplace health. Applied Scientist, Navigation Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way.

We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments.

At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started.

As a Sr. Scientist in Robot Navigation, you will be at the forefront of this transformation — architecting and delivering navigation systems that are intelligent, safe, and scalable.

You will bring deep expertise in learning-based planning and control, a strong understanding of foundation models and their application to embodied agents, and as well as have in-depth understanding of control-theoretic approaches such as model predictive control (MPC)-based trajectory planning. You will develop navigation solutions that seamlessly blend data-driven intelligence with principled control-theoretic guarantees.

Our vision is bold: to build navigation systems that allow robots to move fluidly and safely through dynamic environments — understanding context, anticipating change, and adapting in real time. You will lead research that bridges the gap between cutting-edge academic advances and production grade deployment, collaborating with world-class teams pushing the boundaries of robotic autonomy, manipulation, and human-robot interaction.

Join us in building the next generation of intelligent navigation systems that will define the future of autonomous robotics at scale.

Key job responsibilities - Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding - Lead research initiatives in computer vision, sensor fusion and 3D perception - Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities - Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment - Mentor junior scientists and engineers; contribute to a culture of technical excellence - Define and track key metrics to measure perception system performance in real-world environments - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team Our team is a group is a diverse group of scientists and engineers passionate about building intelligent machines.

We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter. Sr. Applied Scientist, AWS Automated Reasoning Applied Scientist, AWS Automated Reasoning Economist II, GMAC Economics Are you excited about using econometrics, experimentation, and machine learning to impact real-world business decisions?

We are looking for an Economist II to work on challenging problems at the intersection of causal inference and machine learning for Prime Video Ads. You will design experiments, build econometric and ML models, and translate findings into decisions that shape how millions of customers experience advertising on Prime Video.

If you have a deeply quantitative approach to problem-solving, enjoy building and implementing models end-to-end, and want to work on problems where rigorous economics meets production-scale ML, we want to talk to you.

Key job responsibilities - Design, execute, and analyze experiments to measure the impact of ad policies on customer behavior and business outcomes - Develop causal inference models (experimental and observational) to estimate short- and long-term effects of strategic initiatives - Collaborate with scientists, engineers, and product teams to deliver measurable business impact - Influence business leaders based on empirical findings Applied Scientist, AWS Automated Reasoning Applied Scientist, AWS Automated Reasoning Applied Scientist, AWS Automated Reasoning Applied Scientist, AWS Automated Reasoning Sr. Applied Scientist, AWS Automated Reasoning Get more from Amazon Science