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Sustainability call for proposals — Fall 2024

Welcoming proposals related to data validation, life cycle assessment, biodiversity and more.

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About this CFP

Amazon Sustainability works to make Amazon one of the most environmentally and socially responsible places to buy or sell goods and services. We conduct research to map, model and measure the end-to-end environmental and social impact of the company and vet sustainability topics that will have the greatest future impact to Amazon to inform business planning and resilience. We develop and test strategies that support revenue growth while reducing negative environmental and social impact. We work with the external science community to drive our vision and mission. We accelerate sustainability practices at Amazon by guiding critical decision makers with crisp recommendations backed by scientific rigor. We remove ambiguity around sustainability and provide them scientifically credible mechanisms, data, tools and solutions that they can use to make informed decisions.

We welcome proposals in the following research tracks:

Validating sustainability data at scale

Accurate and verifiable greenhouse gas (GHG) emissions data across the supply chain is critical for organizations to make informed procurement decisions, set meaningful carbon and other environmental impacts reduction targets, and drive meaningful progress towards their climate goals. However, the current process of validating supplier-reported GHG metrics is often manual, costly, and lacks consistency. Proving the accuracy of abatement data is further complicated by the complex and ever-changing nature of business operations. Key challenges include verifying that supplier-reported GHG emissions reductions adhere to established standards of being real, additional, and permanent, as well as socially-beneficial. We invite proposals for innovative, open-sourced projects that leverage machine learning (ML) and artificial intelligence (AI) techniques to improve data resolution and validate GHG emissions and carbon accounting data by harnessing data from diverse sources, including data shared by suppliers, with the goal of streamlining the process and lowering the overall cost of verification for all organizations. The validations should be sufficient for GHG emissions and carbon accounting claims. Where possible, we encourage proposals to incorporate current standards for producing (e.g., Product Category Rules) and sharing carbon data (e.g., WBCSD Pathfinder Initiative). Additional challenges include the difficulty in aggregating accurate, comparable GHG emissions data across complex, global supply chains due to inconsistent or costly data sharing practices, and the limited ability for organizations to quickly identify and address discrepancies or anomalies in supplier-reported carbon performance.

Machine learning applications for life cycle assessment

Life cycle assessment (LCA) is an instrumental method for corporations disclosing their environmental footprint. The primary challenges associated with corporate footprinting are scalability, automation, transparency, and lack of appropriate data to measure impacts of a wide range of products and services. Currently, much of the LCA work remains manual, and requires subject matter expertise. We solicit proposals that primarily focus on machine learning application in life cycle assessment ranging from to automating assessment and validation, completing life cycle inventories using approximation, computing product carbon footprint (PCF) in supply chain and BOM data, use of large language models (LLMs) and ontologies / knowledge graphs in LCA settings, and building tools to conduct scenario analysis and assess emissions abatement potential at a web-scale. As lack of groundtruth data is a perennial challenge in this field, proposals are encouraged to contribute open-source benchmark datasets and reduce reliance on large-scale, expensive data collection.

Data-driven sustainable product design and manufacturing

There is a lack of methods, tools, and systems to enable product manufacturers to incorporate sustainability performance metrics into decisions made across the product’s life cycle, from product development to manufacturing to post-use recovery and treatment. We are welcoming research proposals focused on innovative approaches to create, test, and implement decision support capabilities for multiple sustainability criteria (e.g., carbon, waste, and water) to increase the velocity and lower the cost of more sustainable product development. Proposals that demonstrate broad applicability across different product sectors, supply chain complexity, and manufacturing types (discrete and continuous) are highly encouraged.

Climate risk assessment

We invite proposals that leverage novel methods and modeling approaches to advance climate risk assessment and resilience at scale. Traditional methods for monitoring impacts/damages from climate hazards to point assets (e.g. buildings, infrastructure), linear assets (e.g. roads), and supply chains often require expert assessment and are limited in their ability to assess risk at a local level. We seek innovative proposals that utilize artificial intelligence, remote sensing (e.g. pre- and post-disaster imagery), and new modeling techniques to enhance the assessment of vulnerabilities (damage functions). Projects should demonstrate how the proposed approaches can enable scalable, high-resolution risk evaluation without relying on traditional expert assessments. Moreover, proposals investigating the application of emerging technologies to better assess climate-related risks to nature and forests are highly encouraged. Climate risks to forests threaten permanence of carbon storages, durability of nature-based solutions, biodiversity, and supply of commodities within supply chains. We are interested in proposals that use new methodologies to quantify climate-related reversal risks and risks to ecosystem services, for example the inter-connections between carbon, biodiversity, and climate risks. We strongly encourage open-source contributions.

Biodiversity

We request proposals that advance biodiversity measurement, monitoring, and impact assessment. Despite growing recognition of biodiversity risks, critical gaps remain in our ability to systematically quantify changes in ecosystems, species populations, and genetic diversity across spatial scales. Traditional methods for biodiversity assessment have limited scalability, often relying on sparse validation data and expert-driven scoring systems. We invite projects that harness in-situ and remote sampling, artificial-intelligence, and new statistical techniques to enable continuous, high-resolution, and reliable biodiversity tracking at local levels. Additionally, we encourage proposals that advance biodiversity impact quantification and attribution. Innovative approaches are needed to translate the tangible interactions between biodiversity and ecosystems, human systems, and organizations. We are interested in approaches that quantify biodiversity co-benefits of nature-based solutions and climate change mitigation strategies. We encourage open-source contributions and pathways enabling real-world implementation.

Lower-carbon cement and concrete

Amazon seeks research proposals to address a critical gap in validating lower-carbon cement and concrete innovations. Cement and concrete production is highly carbon-intensive, contributing significantly to global emissions. While new solutions emerge, a key challenge is the lack of standardized methods to confirm these new materials can be manufactured, transported, and placed as easily as existing products. We are interested in research that comprehensively evaluates the performance, workability, and constructability of lower-carbon cement and concrete mixes across the value chain. The goal is to generate data-driven evidence supporting broad adoption of sustainable alternatives. Proposals demonstrating collaborative industry partnerships and practical, scalable solutions are encouraged.

Responsible supply chain

Corporate Social Responsibility (CSR) within supply chains is a critical area of research, addressing the ethical, environmental, and social impacts of global supply networks. Traditional supply chain auditing practices, while prevalent, face significant challenges related to scalability, transparency, and the absence of universal evaluation standards. These audits often rely on manual data collection processes, limiting their effectiveness in addressing complex and dynamic social risks.
This call for papers seeks to explore fundamental and academic problems in CSR within supply chains. We invite research that advances the theoretical foundations of CSR in supply chains, particularly through the lens of data-driven approaches and machine learning. Topics of interest include, but are not limited to:

  • Development of universal standards and frameworks for CSR evaluation in global supply chains.
  • Methodologies for real-time social risk detection and hotspot analysis.
  • Predictive modeling for supplier risk assessment and compliance.
  • AI to support humans in performing audits, such as generating strategies and guidance.
  • Innovative strategies for automating and enhancing the transparency of social responsibility audits.
  • Theoretical exploration of the ethical implications of AI in CSR decision-making processes.

CO2 Mineralization

Carbon capture, utilization, and storage (CCUS) is a critical decarbonization lever across several hard-to-abate industrial sectors. However, the potential of carbon capture and storage (CCS) is constrained by the availability of suitable CO2 pipeline infrastructure and nearby geological storage sites. Carbon capture and utilization (CCU) technologies, such as ex-situ mineral carbonation, offer a viable alternative for industrial sites that lack underground storage infrastructure. Nevertheless, the potential of ex-situ carbon mineralization is also limited by the cost of carbonation and the availability of suitable feedstocks besides industrial waste materials. This call for proposals aims to identify solutions that can maximize the impact of mineral carbonation for permanent CO2 sequestration, for example the identification/development of direct carbonation of Mg-rich minerals, processes to broaden the application of magnesium carbonate (MgCO3) produced through mineral carbonation, or AI-driven models for optimization of ex-situ/superficial mineralization.

Timeline

Submission period: September 25, 2024 - November 13, 2024 (11:59PM Pacific Time)

Decision letters will be sent out in March 2025

Award details

Selected Principal Investigators (PIs) may receive the following:

  • Unrestricted funds, from $50,000 to $100,000 USD
  • AWS Promotional Credits, up to $40,000 USD
  • Training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers

Awards are structured as one-year 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.

Eligibility requirements

Please refer to the ARA Program rules on the Rules and Eligibility page.

Proposal requirements

Proposals should be prepared according to the proposal template. In addition, to submit a proposal for this CFP, please also include the following information:

  • Description of the proposed solution and its innovative aspects
  • Explanation of how the project addresses the specified challenges
  • Plan for the development and implementation of the methodology or dataset
  • Potential impact on sustainability in the targeted sectors
  • Inclusion of Category Rules across Environmental Product Declarations and Product Environmental Footprints where applicable
  • List of open-source tools, datasets, or methodologies you plan to contribute to.
  • List of AWS ML tools you will use.

Selection criteria

Proposals will be reviewed by a panel of experts in machine learning, LCA, and sustainability. Proposals will be evaluated on the following:

  • Immediate and sizeable impact on carbon abatements (i.e., reducing greenhouse gases)
  • Practicality and scalability of the solutions that can support measurement validations
  • Feasibility and clarity of the proposed approach
  • Potential for widespread adoption and implementation
  • Feasibility to open source

Expectations from recipients

To the extent deemed reasonable, Award recipients should acknowledge the support from ARA. Award recipients will inform ARA of publications, presentations, code and data releases, blogs/social media posts, and other speaking engagements referencing the results of the supported research or the Award. Award recipients are expected to provide updates and feedback to ARA via surveys or reports on the status of their research. Award recipients will have an opportunity to work with ARA on an informational statement about the awarded project that may be used to generate visibility for their institutions and ARA.

How to apply
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Research Scientist, Design and Simulation, AWS Center for Quantum Computing
US, CA, San Francisco
The AWS Center for Quantum Computing is a multi-disciplinary team of scientists, engineers, and technicians, all working to innovate in quantum computing for the benefit of our customers. We are looking to hire a Research Scientist to design and model novel superconducting quantum devices, including qubits, readout and control schemes, and advanced quantum processors. Candidates with a track record of original scientific contributions and/or software development experience will be preferred. We are looking for candidates with strong engineering principles and resourcefulness. Organization and communication skills are essential. About the team Agentic AI drives innovation at the forefront of artificial intelligence, enabling customers to transform their businesses through cutting-edge AI solutions. We build and deliver the foundational AI services that power the future of cloud computing, helping organizations harness the potential of AI to solve their most complex challenges. Join our dynamic team of AI/ML practitioners, applied scientists, software engineers, and solution architects who work backwards from customer needs to create groundbreaking technologies. If you're passionate about shaping the future of AI while making a meaningful impact for customers worldwide, we want to hear from you. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a U.S export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.
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