Robotics Call for Proposals - Spring 2026 is a grant from Amazon Research Awards that funds academic research advancing the frontier of robotics technology for capable, safe, and intelligent robots operating alongside people in complex real-world environments. Research topics include AI for Robotics and Human-Robot Interaction, Autonomous Navigation, Manipulation in Cluttered and Unstructured Environments, and related areas.

Awards include up to $50,000 USD in unrestricted funds and up to $50,000 USD in AWS Promotional Credits. Eligible applicants are Principal Investigators from academic institutions. Funding decisions are based on potential impact to the research community and quality of scientific content.

The application deadline is May 6, 2026.

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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.

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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. Robotics call for proposals - Spring 2026 Pursuing the future of robotics research. By Amazon Research Awards team Amazon is advancing robotics technology to enable capable, safe, and intelligent robots that can operate alongside people in complex real-world environments.

Amazon Robotics designs, codes, builds, and manufactures game-changing software applications, control systems, robotics, and related hardware that is revolutionizing Amazon's operations across the globe.

We welcome proposals in the following research topics: AI for Robotics and Human-Robot Interaction : Topics of interest include multi-modal perception of complex 3D scenes and situations; multi-modal task grounding from human instructions spanning language, vision, gestures, and references to priors; and understanding long-term object dynamics in environments shared with people.

Areas of interest also include the effects of robot embodiment, and personality expression on user engagement, trust formation, and long-term acceptance in repeated interactions; legibility and transparency of autonomous robot intent, action, and decision-making in collaborative settings; and multi-modal communication strategies for robot error recovery, clarification, and repair in collaborative tasks.

Autonomous Navigation: Relevant areas include geometry-aware navigation accounting for the robot's configuration and payload; integration of multi-modal perception for navigation; reinforcement learning-based control policies for task-specific object interaction (e.g., doors and drawers); and scalable data generation for policy training.

Manipulation in Cluttered and Unstructured Environments : Topics of interest include manipulation under occlusion, stacking, and packing scenarios; compositional approaches to general-purpose manipulation; and non-prehensile manipulation related to contact force sensing and control; compliant control; generalizable surface and sweeping manipulation, impulsive manipulation, use of large multimodal models, and teleoperation.

Physical Reasoning and World Models : Relevant topics include world models learned from multimodal sensory data (vision, force, and tactile); causal reasoning about contact dynamics; semantic abstractions for contact-rich tasks; and simulation and synthetic data for real-world transfer.

Data for Manipulation : Topics of interest include physically grounded scenario and trajectory synthesis, including long-horizon task sequences; cross-embodiment transfer and retargeting; demonstration transfer across manipulation targets; synthetic data augmentation for novel object manipulation; and automated data quality evaluation methods.

Safety-Critical Control and Safe Reinforcement Learning: Relevant areas include safety for manipulation in complex environments; compliant body control and safe contact-rich control; body control robust to external disturbances; verification and monitoring of RL controller performance; safety-constrained reinforcement learning; and robust and verifiable human detection and localization.

Theoretical advances, creative new ideas, and practical applications are all welcome Submission period: March 25 — May 6, 2026 (11:59 PM Pacific Time).

Decision letters will be sent out in August 2026 Selected Principal Investigators (PIs) may receive the following: Unrestricted funds, no more than $50,000 USD on average AWS Promotional Credits, no more than $50,000 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. Robotics 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 The 10 most viewed publications of 2025 From foundation model safety frameworks and formal verification at cloud scale to advanced robotics and multimodal AI reasoning, these are the most viewed publications from Amazon scientists and collaborators in 2025.

The 10 most viewed blog posts of 2025 From quantum computing breakthroughs and foundation models for robotics to the evolution of Amazon Aurora and advances in agentic AI, these are the posts that captured readers' attention in 2025.

Amazon Research Awards recipients announced Amazon Research Awards team Awardees, who represent 41 universities in 8 countries, have access to Amazon public datasets, along with AWS AI/ML services and tools.

Senior Data Scientist, Amazon Stores Finance Science, Amazon Stores Finance Science WW Amazon Stores Finance Science (ASFS) works to leverage science and economics to drive improved financial results, foster data backed decisions, and embed science within Finance.

ASFS is focused on developing products that empower controllership, improve business decisions and financial planning by understanding financial drivers, and innovate science capabilities for efficiency and scale. We are looking for a data scientist to lead high visibility initiatives for forecasting Amazon Stores' financials.

You will develop new science-based forecasting methodologies and build scalable models to improve financial decision making and planning for senior leadership up to VP and SVP level. You will build new ML and statistical models from the ground up that aim to transform financial planning for Amazon Stores.

We prize creative problem solvers with the ability to draw on an expansive methodological toolkit to transform financial decision-making with science. The ideal candidate combines data-science acumen with strong business judgment. You have versatile modeling skills and are comfortable owning and extracting insights from data.

You are excited to learn from and alongside seasoned scientists, engineers, and business leaders. You are an excellent communicator and effectively translate technical findings into business action.

Key job responsibilities Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models Working with technical and non-technical stakeholders across every step of science project life cycle Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models Innovating by adapting new modeling techniques and procedures Presenting research results to our internal research community Economist I, Stores Economics and Science This role will contribute to developing the Economics and Science products and services in the Fee domain, with specialization in supply chain systems and fees.

Through the lens of economics, you will develop causal links for how Amazon, Sellers and Customers interact. You will be a key and senior scientist, advising Amazon leaders how to price our services. You will work on developing frameworks and scalable, repeatable models supporting optimal pricing and policy in the two-sided marketplace that is central to Amazon's business.

The pricing for Amazon services is complex. You will partner with science and technology teams across Amazon including Advertising, Supply Chain, Operations, Prime, Consumer Pricing, and Finance. We are looking for an experienced Economist to improve our understanding of seller Economics, enhance our ability to estimate the causal impact of fees, and work with partner teams to design pricing policy changes.

In this role, you will provide guidance to scientists to develop econometric models to influence our fee pricing worldwide. You will lead the development of causal models to help isolate the impact of fee and policy changes from other business actions, using experiments when possible, or observational data when not.

Key job responsibilities The ideal candidate will have extensive Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results.

They will work closely with Economists, Data / Applied Scientists, Strategy Analysts, Data Engineers, and Product leads to integrate economic insights into policy and systems production. Familiarity with systems and services that constitute seller supply chains is a plus but not required. About the team The Stores Economics and Sciences team is a central science team that supports Amazon's Retail and Supply Chain leadership.

We tackle some of Amazon's most challenging economics and machine learning problems, where our mandate is to impact the business on massive scale. Intern - Economics, Return And Recommerce Economics Intelligence We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference and/or structural econometrics skillsets to solve real world problems.

The intern will work in the area of Economics Intelligence in Amazon Returns and Recommerce Technology and Innovation and develop new, data-driven solutions to support the most critical components of this rapidly scaling team. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development.

Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement.

These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The WWRR Economics Intelligence (RREI) team brings together Economists, Data Scientists, and Business Intelligence Engineers experts to delivers economic solutions focused on forecasting, causality, attribution, customer behavior for returns, recommerce, and sustainability domains.

Intern - Economics, Return And Recommerce Economics Intelligence We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference and/or structural econometrics skillsets to solve real world problems.

The intern will work in the area of Economics Intelligence in Amazon Returns and Recommerce Technology and Innovation and develop new, data-driven solutions to support the most critical components of this rapidly scaling team. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development.

Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement.

These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The WWRR Economics Intelligence (RREI) team brings together Economists, Data Scientists, and Business Intelligence Engineers experts to delivers economic solutions focused on forecasting, causality, attribution, customer behavior for returns, recommerce, and sustainability domains.

Research Scientist, Special Projects Innovators wanted! Are you an entrepreneur? A builder?

A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the next level. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers.

No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As a Research Scientist, you will work with a unique and gifted team developing exciting products for consumers and collaborate with cross-functional teams.

Our team rewards intellectual curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment.

At the intersection of both academic and applied research in this product area, you have the opportunity to work together with some of the most talented scientists, engineers, and product managers. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion.

We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.

Senior Applied Scientist, New Initiatives Amazon has co-founded and signed The Climate Pledge, a commitment to reach net zero carbon by 2040. As a team, we leverage GenAI, sensors, smart home devices, cloud services, material science, and Alexa to build products that have a meaningful impact for customers and the climate.

In alignment with this bold corporate goal, the Amazon Devices & Services organization is looking for a passionate, talented, and inventive Senior Applied Scientist to help build revolutionary products with potential for major societal impact. Great candidates for this position will have expertise in the areas of agentic AI applications, deep learning, time series analysis, LLMs, and multimodal systems.

This includes experience designing autonomous AI agents that can reason, plan, and execute multi-step tasks, building tool-augmented LLM systems with access to external APIs and data sources, implementing multi-agent orchestration, and developing RAG architectures that combine LLMs with domain-specific knowledge bases. You will strive for simplicity and creativity, demonstrating high judgment backed by statistical proof.

Key job responsibilities As a Senior Applied Scientist on the Energy Science team, you'll design and deploy agentic AI systems that autonomously analyze data, plan solutions, and execute recommendations.

You'll build multi-agent architectures where specialized AI agents coordinate to solve complex optimization problems, and develop tool-augmented LLM applications that integrate with external data sources and APIs to deliver context-aware insights. Your work involves creating multimodal AI systems that synthesize diverse data streams, while implementing RAG pipelines that ground large language models in domain-specific knowledge bases.

You'll apply advanced machine learning and deep learning techniques to time series analysis, forecasting, and pattern recognition. Beyond technical innovation, you'll drive end-to-end product development from research through production deployment, collaborating with cross-functional teams to translate AI capabilities into customer experiences.

You'll establish rigorous experimentation frameworks to validate model performance and measure business impact, building AI-driven products with potential for major societal impact. Applied Scientist II, HST Health Evaluation Amazon Health Services (One Medical) About Us: At Health AI, we're revolutionizing healthcare delivery through innovative AI-enabled solutions.

As part of Amazon Health Services and One Medical, we're on a mission to make quality healthcare more accessible while improving patient outcomes. Our work directly impacts millions of lives by empowering patients and enabling healthcare providers to deliver more meaningful care. Role Overview: We're seeking an Applied Scientist to join our dynamic team in building state of the art AI/ML solutions for healthcare.

This role offers a unique opportunity to work at the intersection of artificial intelligence and healthcare, developing solutions that will shape the future of medical services delivery.

Key job responsibilities • Lead end-to-end development of AI/ML solutions for Amazon Health organization, including Amazon Pharmacy and One Medical • Research, design, and implement state-of-the-art machine learning models, with a focus on Large Language Models (LLMs) and Visual Language Models (VLMs) • Optimize and fine-tune models for production deployment, including model distillation for improved latency • Drive scientific innovation while maintaining a strong focus on practical business outcomes • Collaborate with cross-functional teams to translate complex technical solutions into tangible customer benefits • Contribute to the broader Amazon Health scientific community and help shape our technical roadmap Member of Technical Staff, Engineering Manager , Amazon AGI Lab Amazon launched the AGI Lab to develop foundational capabilities for useful AI agents.

We built Nova Act - a new AI model trained to perform actions within a web browser. The team builds AI/ML infrastructure that powers our production systems to run performantly at high scale. We’re also enabling practical AI to make our customers more productive, empowered, and fulfilled.

In particular, our work combines large language models (LLMs) with reinforcement learning (RL) to solve reasoning, planning, and world modeling in both virtual and physical environments. Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research.

We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up! Key job responsibilities This role will lead a team of SDEs building AI agents infrastructure from launch to scale.

The role requires the ability to span across ML/AI system architecture and infrastructure. You will work closely with application developers and scientists to have a impact on the Agentic AI industry. We're looking for a Software Development Manager who is energized by building high performance systems, making an impact and thrives in fast-paced, collaborative environments.

About the team Check out the Nova Act tools our team built on on nova. amazon.

com/act Applied Scientist III - AMZ9674037 MULTIPLE POSITIONS AVAILABLE Employer: AMAZON WEB SERVICES, INC. Offered Position: Applied Scientist III Job Location: Seattle, Washington Job Number: AMZ9674037 Position Responsibilities: Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications.

Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data, and run and analyze experiments in a production environment. Identify new opportunities for research in order to meet business goals.

Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. Position Requirements: Master’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and two years of research or work experience in the job offered, or as a Research Scientist, Research Assistant, Software Engineer, or a related occupation.

Employer will accept a Bachelor’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and five years of progressive post-baccalaureate research or work experience in the job offered or a related occupation as equivalent to the Master’s degree and two years of research or work experience.

Must have one year of research or work experience in the following skill(s): (1) programming in Java, C++, Python, or equivalent programming language; and (2) conducting the analysis and development of various supervised and unsupervised machine learning models for moderately complex projects in business, science, or engineering. Amazon.

com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $167,100/year to $226,100/year. Amazon is a total compensation company.

Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www. aboutamazon.

com/workplace/employee-benefits. #0000 Data Scientist, AWS Quick Data Amazon Quick Suite is an enterprise AI platform that transforms how organizations work with their data and knowledge. Combining generative AI-powered search, deep research capabilities, intelligent agents and automations, and comprehensive business intelligence, Quick Suite serves tens of thousands of users.

Our platform processes thousands of queries monthly, helping teams make faster, data-driven decisions while maintaining enterprise-grade security and governance. From natural language interactions with complex datasets to automated workflows and custom AI agents, Quick Suite is redefining workplace productivity at unprecedented scale.

We are seeking a Data Scientist II to join our Quick Data team, focusing on evaluation and benchmarking data development for Quick Suite features, with particular emphasis on Research and other generative AI capabilities. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Quick Suite.

From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users at scale. As part of our diverse team—including data scientists, engineers, language engineers, linguists, and program managers—you will collaborate closely with science, engineering, and product teams.

We are driven by customer obsession and a commitment to excellence. Key job responsibilities In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions.

Specific responsibilities include: * Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features * Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings * Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases * Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance * Develop and refine annotation guidelines and quality frameworks for evaluation tasks * Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies * Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements * Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts * Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets About the team Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious.

Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer.

That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture.

When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face.

Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices. Collaborating with scientists around the world to fund research, share knowledge and encourage innovation. Get more from Amazon Science