Exciting Research Opportunities in AI and Computer Vision for Sports Analytics at KAUST

Fields: Computer Science, Artificial Intelligence, Data Science, Electrical Engineering, Sports Analytics

Are you passionate about harnessing cutting-edge artificial intelligence and computer vision to revolutionize the world of sports analytics? Do you aspire to collaborate with global leaders and contribute to high-impact research that shapes the future of sports technology?

Introduction

King Abdullah University of Science and Technology (KAUST), a leading international graduate-level research university located on the Red Sea coast of Saudi Arabia, is renowned for its innovative research environment, world-class facilities, and vibrant international community. KAUST’s commitment to advancing science and technology is exemplified by the SoccerNet project, a pioneering initiative at the intersection of artificial intelligence (AI), computer vision (CV), and sports analytics. As the project expands its research scope and collaborative reach, we are seeking talented and motivated Visiting PhD Students, Postdoctoral Researchers, and Research Engineers to join our dynamic team.

About The Research Topic And Project

The SoccerNet project at KAUST is at the forefront of AI and computer vision applications for sports, with a special focus on football (soccer). The research encompasses a diverse range of topics, including action spotting, video captioning, player tracking, and game state reconstruction. As the field of sports analytics evolves, the project is pushing boundaries into next-generation domains such as foundation models, multi-modal AI, explainability, and agentic AI. These advancements are designed to deliver deeper insights, enhanced decision-making, and transformative experiences for athletes, coaches, broadcasters, and fans alike.

Central to the SoccerNet initiative is the development and utilization of large-scale datasets and benchmarks (see https://www.soccer-net.org), which enable the creation and validation of state-of-the-art AI and CV algorithms. The project also emphasizes open science and reproducibility, contributing tools and resources to the broader research community (see https://lnkd.in/ghGEzB5x).

Importance of the Topic in Today’s World

AI-driven sports analytics is rapidly transforming the way games are played, analyzed, and experienced. With the explosion of data from high-resolution cameras, wearables, and broadcast feeds, extracting actionable insights in real time has become a cornerstone of competitive advantage in professional sports. The integration of explainable and agentic AI models further opens new avenues for transparency, strategy optimization, and fan engagement. By joining this project, researchers have the unique opportunity to contribute to a field that not only advances fundamental science but also has tangible societal and commercial impact.

About The Lab And Supervisor

The SoccerNet project is led by Dr. Silvio Giancola, an accomplished researcher in AI and computer vision, known for fostering a collaborative and innovative research culture. The lab maintains strong partnerships with leading organizations such as FIFA, top-tier football clubs, and major broadcasters, providing unparalleled opportunities for global collaboration and real-world impact. Team members regularly publish at premier AI and CV conferences, ensuring that their research is recognized at the highest levels.

Benefits of Conducting Research at KAUST

KAUST Offers a Stimulating Research Environment Characterized By State-of-the-art Computational Resources, Generous Funding, And An International, Interdisciplinary Community. Researchers Benefit From

– Access to world-class facilities and datasets

– Collaboration with leading industry and academic partners

– Opportunities to publish and present at top conferences

– Support for open-source contributions and community engagement

– A multicultural campus with outstanding quality of life and professional development resources

Ideal Candidate Profile

We are seeking candidates with a strong background in AI, computer vision, or deep learning, and a demonstrated interest in sports analytics and next-generation AI topics (such as multi-modal, explainable, or agentic AI). Successful candidates will have experience publishing in top-tier research venues and a passion for driving innovation in applied and fundamental research.

Requirements

– Background in Artificial Intelligence, Computer Vision, or Deep Learning

– Experience publishing research papers in top-tier conferences or journals

– Demonstrated interest in sports analytics and next-generation AI (multi-modal, explainable, agentic)

– Strong programming and analytical skills

– Ability to work collaboratively in an international team environment

Application and Contact Information

To Apply, Please Send The Following Documents

– Curriculum Vitae (CV)

– Motivation Letter

– Research Statement

Send your application to: silvio [dot] giancola [at] kaust [dot] edu [dot] sa

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