UT Austin campus tower is seen on a sunny day, there are students walking in the foreground
Amazon and the University of Texas at Austin have announced the launch of the UT Austin-Amazon Science Hub. The hub’s goals are to advance research that prompts new discoveries and addresses significant challenges while creating solutions whose benefits are shared broadly across all sectors of society.
UT Austin

Amazon and University of Texas at Austin launch Science Hub

The collaboration supports education, community outreach, and the application of academic research to video streaming and robotics.

Amazon and the University of Texas at Austin (UT Austin) have announced the launch of the UT Austin-Amazon Science Hub, continuing Amazon’s commitment to supporting academic research.

The hub’s goals are to advance research that prompts new discoveries and addresses significant challenges while creating solutions whose benefits are shared broadly across all sectors of society. This will be achieved by fostering collaboration among leading scholars, including faculty and students, along with the development of a diverse and sustainable pipeline of research talent. The initial areas of focus will include video streaming, search and information retrieval, and robotics.

The exterior of UT Austin’s Cockrell School of Engineering
As part of the collaboration, which will be hosted in UT Austin’s Cockrell School of Engineering, Amazon will provide funding for research projects, PhD graduate student fellowships, and community-building events.
UT Austin

As part of the collaboration, which will be hosted in UT Austin’s Cockrell School of Engineering, Amazon will provide funding for research projects, PhD graduate student fellowships, and community-building events designed to diversify and increase cross-disciplinary innovation. The inaugural event, open to all UT Austin research staff and research students, will be held April 12 on the UT Austin campus.

“Amazon is thrilled to establish a university hub at UT Austin,” said BA Winston, vice president of technology at Prime Video. “For years, our top scientists have been a resource to UT Austin graduate students collaborating on topics such as developing objective machine learning models to predict perceptual video quality, which drives smart compression, and multimodal AI models that help ensure the highest-quality media playback experience at scale.”

“We are striving to establish even more collaborations with leading companies and organizations in order to bring together more talented people, produce higher-impact research, and help our students reach their greatest ambitions. The launch of the new hub with Amazon is the latest success story in this effort,” said UT Austin President Jay Hartzell. “I am eager to see the discoveries that our researchers and students will create from this collaboration and how those discoveries will change the world.”

The UT Austin band is seen playing on the field
The initial areas of focus of the UT-Austin Amazon Science Hub will include video streaming, search and information retrieval, and robotics.
UT Austin

Amazon has extensive ties to UT Austin via the Amazon Scholars program. James Bornholt, an assistant professor in the Department of Computer Science, whose research is focused on programming languages and formal methods, has worked as a Scholar with Amazon Web Services since 2022. Deepayan Chakrabarti, a Scholar in the Customer Trust organization, is also an associate professor of information, risk, and operations management who researches a broad range of challenges, including large-graph mining and problems of limited data. Shuchi Chawla, a professor of computer science, works as a Scholar in Amazon Ads, where she applies her background in problems that involve stochastic input, online decision-making, uncertainty, and learning.

Matthew Lease, a professor in the School of Information and a Scholar with AWS, is also the head of the Laboratory for Artificial Intelligence and Human-Centered Computing, where his research integrates AI with human-computer-interaction techniques. Ayşegül Şahin, the Richard J. Gonzalez Regents Chair in Economics at UT Austin and a Scholar at Amazon, spent 14 years as a research economist at the Federal Reserve Bank of New York, where she founded and led the team that focused on the analysis of the US labor market. Sujay Sanghavi, associate professor of electrical and computer engineering, is both a principal research scientist and Scholar with Amazon Search. He also serves as the director of the NSF TRIPODS (Transdisciplinary Research in Principles of Data Science) Institute for Data Science.

austin-city-skyline-near-first-street-bridge.jpg
Amazon researchers in Austin are addressing challenges including supply chain optimization, transportation management, and data science.
UT Austin

“This Science Hub will strengthen the partnership between UT Austin and Amazon by leveraging our collective strengths and creating opportunities for our faculty and students and leaders at Amazon to work together to accelerate progress in the areas of computer vision, ML, AI, and robotics,” said Roger Bonnecaze, dean of the Cockrell School of Engineering.

“UT Austin has built an impressive program in robotics, with exceptional faculty and students,” said Ken Washington, vice president of Amazon Consumer Robotics. “The new hub will allow us to collaborate even more closely with them in robotics and related disciplines, so I’m very optimistic about our growing partnership.”

The establishment of the UT Austin Science Hub builds upon Amazon’s existing research efforts in Austin. Amazon researchers in Austin are addressing challenges including supply chain optimization, transportation management, and data science.

In addition, several researchers at UT-Austin are recipients of Amazon Research Awards, including Ying Ding, the Bill and Lewis Suit Professor in the School of Information, and Jon Tamir, assistant professor of electrical and computer engineering.

Founded in 1883, UT Austin is a leading public research institution, attracting more than $650 million annually. More than 52,000 students and 3,000 teaching faculty compose the university’s 18 colleges and schools. UT Austin was ranked first among US universities in research financed by the US National Science Foundation (NSF) in 2020, according to the annual Higher Education Research and Development (HERD) survey.

“With this hub, I look forward to seeing more cutting-edge research that will not only enhance our customer experience but also help us envision longer-term research goals,” Winston said.

Related content

US, CA, Santa Clara
AWS AI is looking for passionate, talented, and inventive Research Scientists with a strong machine learning background to help build industry-leading Conversational AI Systems. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Understanding (NLU), Dialog Systems including Generative AI with Large Language Models (LLMs) and Applied Machine Learning (ML). As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services that make use language technology. You will gain hands on experience with Amazon’s heterogeneous text, structured data sources, and large-scale computing resources to accelerate advances in language understanding. We are hiring in all areas of human language technology: NLU, Dialog Management, Conversational AI, LLMs and Generative AI. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the 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. Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. 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 (gender diversity) 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.
US, VA, Herndon
Machine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations. The Generative AI team helps AWS customers accelerate the use of Generative AI to solve business and operational challenges and promote innovation in their organization. As an applied scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for talented scientists capable of applying ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others. Key job responsibilities The primary responsibilities of this role are to: • Design, develop, and evaluate innovative ML models to solve diverse challenges and opportunities across industries • Interact with customer directly to understand their business problems, and help them with defining and implementing scalable Generative AI solutions to solve them • Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new solution About the team ABOUT AWS: Diverse Experiences Amazon 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. 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. 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 (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship and 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.
US, WA, Seattle
Our team's mission is to improve Shopping experience for customers interacting with Amazon devices via voice. We research and develop advanced state-of-the-art speech and language modeling technologies. Do you want to be part of the team developing the latest technology that impacts the customer experience of ground-breaking products? Then come join us and make history. Key job responsibilities We are looking for a passionate, talented, and inventive Applied Scientist with a background in Machine Learning to help build industry-leading Speech and Language technology. As an Applied Scientist at Amazon you will work with talented peers to develop novel algorithms and modelling techniques to drive the state of the art in speech synthesis. Position Responsibilities: * Participate in the design, development, evaluation, deployment and updating of data-driven models for Speech and Language applications. * Participate in research activities including the application and evaluation of Speech and Language techniques for novel applications. * Research and implement novel ML and statistical approaches to add value to the business. * Mentor junior engineers and scientists.
CN, 31, Shanghai
The AWS Shanghai AI Lab is looking for a passionate, talented, and inventive staff in all AI domains with a strong machine learning background as an Applied Scientist. Founded in 2018, the Shanghai Lab has been an innovation center of for long-term research projects across domains as machine learning, computer vision, natural language processing, and open-source AI system. Meanwhile, these incubated projects power products across various AWS services. As part of the lablet, you will take a leadership role and join a vibrant team with a diverse set of expertise in both machine learning and applicational domains. You will work on state-of-the-art solutions on fundamental research problems with other world-class scientists and engineers in AWS around the globe and across the boarders. You will have the responsibility to design and innovate solutions to our customers. You will build models to tame large amount of data, achieve industry-level scalability and efficiency, and along the way rapidly grow and build the team.
US, WA, Bellevue
Amazon is looking for an outstanding Senior Economist to help build next generation selection/assortment systems. On the Specialized Selection team within the Supply Chain Optimization Technologies (SCOT) organization, we own the selection to determine which products Amazon offers in our fastest delivery programs. We build tools and systems that enable our partners and business owners to scale themselves by leveraging our problem domain expertise, focusing instead on introspecting our outputs and iteratively helping us improve our ML models rather than hand-managing their assortment. We partner closely with our business stakeholders as we work to develop state-of-the-art, scalable, automated selection. Our team is highly cross-functional and employs a wide array of scientific tools and techniques to solve key challenges, including supervised and unsupervised machine learning, non-convex optimization, causal inference, natural language processing, linear programming, reinforcement learning, and other forecast algorithms. Some critical research areas in our space include modeling substitutability between similar products, incorporating basket awareness and complementarity-aware logic, measuring speed sensitivity of products, modeling network capacity constraints, and supply and demand forecasting. We're looking for a candidate with a background in experiment design and causal analysis to lead studies related to selection and speed. Potential projects include understanding the short-term and long-term customer impact of assortment changes across different speed. As an Senior Economist, you'll build econometric models using our world-class data systems and apply economic theory to solve business problems in a fast-moving environment. You will work with software engineers, product managers, and business teams to understand the business problems and requirements, distill that understanding to crisply define the problem, and design and develop innovative solutions to address them. To be successful in this role, you'll need to communicate effectively with product and tech teams, and translate data-driven findings into actionable insights. You'll thrive if you enjoy tackling ambiguous challenges using the economics toolkit and identifying and solving problems at scale. We have a supportive, fast-paced team culture, and we prioritize learning, growth, and helping each other continuously raise the bar. Key job responsibilities - Lead data-driven econometric studies to create future business opportunities - Consult with stakeholders in Selection and other teams to help solve existing business challenges - Independently identify and pursue new opportunities to leverage economic insights - Advise senior leaders and collaborate with other scientists to drive innovation - Support innovative delivery program growth worldwide - Write business and technical documents communicating business context, methods, and results to business leadership and other scientists - Serve as a technical lead and mentor for junior scientists, ensuring a high science bar - Serve as a technical reviewer for our team and related teams, including document and code reviews
US, CA, Pasadena
The Amazon Web Services (AWS) Center for Quantum Computing in Pasadena, CA, is looking to hire a Research Scientist specializing the design of microwave components for cryogenic environments. Working alongside other scientists and engineers, you will design and validate hardware performing microwave signal conditioning at cryogenic temperatures for AWS quantum processors. Candidates must have a background in both microwave theory and implementation. Working effectively within a cross-functional team environment is critical. The ideal candidate will have a proven track record of hardware development from requirements development to validation. Key job responsibilities Our scientists and engineers collaborate across diverse teams and projects to offer state of the art, cost effective solutions for the signal conditioning of AWS quantum processor systems at cryogenic temperatures. You’ll bring a passion for innovation, collaboration, and mentoring to: Solve layered technical problems across our cryogenic signal chain. Develop requirements with key system stakeholders, including quantum device, test and measurement, cryogenic hardware, and theory teams. Design, implement, test, deploy, and maintain innovative solutions that meet both performance and cost metrics. Research enabling technologies necessary for AWS to produce commercially viable quantum computers. A day in the life As you design and implement cryogenic microwave signal conditioning solutions, from requirements definition to deployment, you will also: Participate in requirements, design, and test reviews and communicate with internal stakeholders. Work cross-functionally to help drive decisions using your unique technical background and skill set. Refine and define standards and processes for operational excellence. Work in a high-paced, startup-like environment where you are provided the resources to innovate quickly. About the team AWS values diverse experiences. Even if you do not meet all of the 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.
US, CA, San Francisco
We are seeking a highly motivated PhD Research Scientist Intern to join our robotics teams at Amazon. This internship offers a unique opportunity to work on cutting-edge robotics projects that directly impact millions of customers worldwide. You will collaborate with world-class experts, tackle groundbreaking research problems, and contribute to the development of innovative solutions that shape the future of robotics and artificial intelligence. As a Research Scientist intern, you will be challenged to apply theory into practice through experimentation and invention, develop new algorithms using modeling software and programming techniques for complex problems, implement prototypes, and work with massive datasets. You'll find yourself at the forefront of innovation, working with large language models, multi-modal models, and modern reinforcement learning techniques, especially as applied to real-world robots. Imagine waking up each morning, fueled by the excitement of solving intricate puzzles that have a direct impact on Amazon's operational excellence. Your day might begin by collaborating with cross-functional teams, exchanging ideas and insights to develop innovative solutions in robotics and AI. You'll then immerse yourself in a world of data and algorithms, leveraging your expertise in large language models and multi-modal systems to uncover hidden patterns and drive operational efficiencies. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Amazon has positions available for Research Scientist Internships in, but not limited to, Bellevue, WA; Boston, MA; Cambridge, MA; New York, NY; Santa Clara, CA; Seattle, WA; Sunnyvale, CA, and San Francisco, CA. We are particularly interested in candidates with expertise in: Robotics, Computer Vision, Artificial Intelligence, Causal Inference, Time Series, Large Language Models, Multi-Modal Models, and Reinforcement Learning. In this role, you gain hands-on experience in applying cutting-edge analytical and AI techniques to tackle complex business challenges at scale. If you are passionate about using data-driven insights and advanced AI models to drive operational excellence in robotics, we encourage you to apply. The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail, and have the ability to thrive in a fast-paced, ever-changing environment. A day in the life Work alongside global experts to develop and implement novel scalable algorithms in robotics, incorporating large language models and multi-modal systems. Develop modeling techniques that advance the state-of-the-art in areas of robotics, particularly focusing on modern reinforcement learning for real-world robotic applications. Anticipate technological advances and work with leading-edge technology in AI and robotics. Collaborate with Amazon scientists and cross-functional teams to develop and deploy cutting-edge robotics solutions into production, leveraging the latest in language models and multi-modal AI. Contribute to technical white papers, create technical roadmaps, and drive production-level projects that support Amazon Science in the intersection of robotics and advanced AI. Embrace ambiguity, maintain strong attention to detail, and thrive in a fast-paced, ever-changing environment at the forefront of AI and robotics research.
US, WA, Seattle
Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. How do you get items to customers quickly, cost-effectively, and—most importantly—safely, in less than an hour? And how do you do it in a way that can scale? Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that! We are delivering to customers, and are excited for what’s to come. Check out more information about Prime Air on the About Amazon blog (https://www.aboutamazon.com/news/transportation/amazon-prime-air-delivery-drone-reveal-photos). If you are seeking an iterative environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide benefits to customers, Prime Air is the place for you. Come work on the Amazon Prime Air Team! Our Prime Air Drone Vehicle Design and Test team within Flight Sciences is looking for an outstanding engineer to help us rapidly configure, design, analyze, prototype, and test innovative drone vehicles. You’ll be responsible for assessing the Aerodynamics, Performance, and Stability & Control characteristics of vehicle designs. You’ll help build and utilize our suite of Multi-disciplinary Optimization (MDO) tools. You’ll explore new and novel drone vehicle conceptual designs in both focused and wide open design spaces, with the ultimate goal of meeting our customer requirements. You’ll have the opportunity to prototype vehicle designs and support wind tunnel and other testing of vehicle designs. You will directly support the Office of the Chief Program Engineer, and work closely across all vehicle subsystem teams to ensure integrated designs that meet performance, reliability, operability, manufacturing, and cost requirements. About the team Our Flight Sciences Vehicle Design & Test organization includes teams that span the following disciplines: Aerodynamics, Performance, Stability & Control, Configuration & Spatial Integration, Loads, Structures, Mass Properties, Multi-disciplinary Optimization (MDO), Wind Tunnel Testing, Noise Testing, Flight Test Instrumentation, and Rapid Prototyping.
US, WA, Seattle
This is a unique opportunity to build technology and science that millions of people will use every day. Are you excited about working on large scale Natural Language Processing (NLP), Machine Learning (ML), and Large Language Models (LLM)? We are embarking on a multi-year journey to improve the shopping experience for customers using Alexa globally. In 2024, we started building all Shopping experiences leveraging LLMs in the US. We create customer-focused solutions and technologies that makes shopping delightful and effortless for our customers. Our goal is to understand what customers are looking for in whatever language happens to be their choice at the moment and help them find what they need in Amazon's vast catalog of billions of products. We are seeking an Applied Scientist to lead a new, greenfield initiative that shapes the arc of invention with Machine Learning and Large Language Models. Your deliverables will directly impact executive leadership team goals and shape the future of shopping experiences with Alexa. We’re working to improve shopping on Amazon using the conversational capabilities of LLMs, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You'll be working with talented scientists, engineers, across the breadth of Amazon Shopping and AGI to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!
US, WA, Seattle
The vision for Alexa is to be the world’s best personal assistant. Such an assistant will play a vital role in managing the communication lives of customers, from drafting communications to coordinating with people on behalf of customers. At Alexa Communications, we’re leveraging Generative AI to bring this vision to life. If you’re passionate about building magical experiences for customers, while solving hard, complex technical problems, then this role is for you. You will operate at the intersection of large language models, real time communications, voice and graphical user interfaces, and mixed reality to deliver cutting-edge features for end users. Come join us to invent the future of how millions of customers will communicate with and through their virtual AI assistants. Key job responsibilities The Comms Experience Insights (CXI) team is looking for an experienced, self-driven, analytical, and strategic Data Scientist II. We are looking for an individual who is passionate about tying together huge amounts of data to answer complex stakeholder questions. You should have deep expertise in translating data into meaningful insights through collaboration with Data Engineers and Business Analysts. You should also have extensive experience in model fitting and explaining how the insights derived from those models impact a business. In this role, you will take data curated by a dedicated team of Data Engineers to conduct deep statistical analysis on usage trends. The right candidate will possess excellent business and communication skills, be able to work with business owners to develop and define key business questions, and be able to collaborate with Data Engineers and Business Analysts to analyze data that will answer those questions. The right candidate should have a solid understanding of how to curate the right datasets that can be used to train data models, and the desire to learn and implement new technologies and services to further a scalable, self-service model.