Postdoctoral Position in Soccer Analytics
100%, Zurich, fixed-termPosted Sep 7, 2026
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Postdoctoral Position in Soccer Analytics
100%, Zurich, fixed-term
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The Algorithms and Visualization Group in the Social Networks Lab at ETH Zürich is headed by Prof. Dr. Ulrik Brandes. We develop network data science methods for applications in a variety of domains. To further our research in sports analytics we seek to expand the team with a postdoctoral researcher. The position is intended for an initial period of two years, but starting date and duration are flexible. High-quality event and tracking data are changing the way association football (soccer) is analyzed and presented. We aspire to move to the forefront of this development by exploring innovative approaches and trying them in practice.
Job description
• Conduct research on methods for match and performance analysis
• Teach and supervise students
• Collaborate with stakeholders in professional football
• Develop your own research agenda and profile
• Take one for the team
Profile
• Doctoral degree in computer science, mathematics, statistics, or similar; candidates with a degree in (any) sports and a strong computational leaning are equally welcome
• Enthusiasm for data and sports, including football
• A curious, creative, and critical attitude
• Interest in theory, empirical research, and substantive interpretation
• Excellent written and spoken English; German a plus
Workplace
Workplace
We offer
• Research as a team sport
• Access to professionals and data
• Mentoring and career development
• Excellent working conditions
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Working, teaching and research at ETH Zurich
We value diversity and sustainability
In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate-neutral future.
Curious? So are we.
We look forward to receiving your online application with the following documents:
• A curriculum vitae including contact information of 2-3 referees
• A letter demonstrating your suitability for this position and your career goals
• Your publication list and a statement about your three most important achievements
• Doctoral degree certificate (or confirmation of scheduled completion date) and full transcripts of your master degree (or equivalent)
Further information about the Social Networks Lab can be found on our Website. Questions regarding the position should be directed to Prof. Brandes, ubrandes@ethz.ch (no applications).
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.
About ETH Zürich
ETH Zurich is one of the world’s leading universities specialising in
science and technology. We are renowned for our excellent education,
cutting-edge fundamental research and direct transfer of new knowledge
into society. Over 30,000 people from more than 120 countries find our
university to be a place that promotes independent thinking and an
environment that inspires excellence. Located in the heart of Europe,
yet forging connections all over the world, we work together to
develop solutions for the global challenges of today and tomorrow.
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Original posting: jobs.ethz.ch
RISC-V ecosystem
ETH Zurich in the RISC-V ecosystem
RISC-V International: Community
Founded in 1855, Swiss Federal Institute of Technology is a science, technology, mathematics, engineering, and management university in Zurich, Switzerland.
- Designs RISC-V research processors: the Snitch RISC-V core (reported sixfold performance gains)
- Ultra-low-power RISC-V clusters from its PULP-family research (e.g. Dustin 16-core cluster, in-memory-computing inference clusters)
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