ETH Zurich is providing a great opportunity through the PhD Position in Decentralized Resource-Constrained Machine Learning in Switzerland. The opportunity is available to talented students for the academic year 2025-2026.
To be eligible for the PhD position at ETH Zurich, applicants must hold or be about to complete a master’s degree in Computer Science, Engineering, Mathematics, or a closely related field by September 1, 2025. They should have a strong academic record, proven experience in areas such as machine learning, distributed systems, or optimization, and solid programming skills, particularly in Python and PyTorch.
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Award
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Application Process
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Clarity of Information
User Review
( votes)ETH Zurich –Swiss Federal Institute of Technology is one of the world’s leading universities for science, engineering, and technology. Located in Zurich, Switzerland, it is renowned for its cutting-edge research, innovation, and academic excellence. Established in 1855, ETH Zurich has produced numerous Nobel laureates and plays a key role in advancing knowledge in fields such as computer science, physics, and environmental science.
Application Deadline: Open
Brief Description
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University or Organization: ETH Zurich
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Department: Distributed Computing (DISCO) Group
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Course Level: PhD
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Award: PhD position (100%)
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Access Mode: Online
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Number of Awards: One
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Nationality: Open to international students
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The award can be taken in: Switzerland
Eligibility
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Eligible Countries: All nationalities
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Acceptable Course or Subjects: The scholarship will be awarded for a PhD in Decentralized Machine Learning, Distributed Systems, or related fields, aligned with the project scope in computer science, engineering, or mathematics.
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Admissible Criteria: To be eligible, applicants must:
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Hold or be about to obtain a Master’s degree in Computer Science, Engineering, Mathematics, or a related field by 1 September 2025.
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Demonstrate strong academic performance with a solid Transcript of Records.
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Show theoretical and practical experience in at least one of the following topics:
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Federated/Deep/Split Learning, Neural Architecture Search, Online Algorithms, Resource-Constrained Networking, Optimization, etc.
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Have proficiency in Python and experience with PyTorch or similar ML frameworks.
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Exhibit strong English communication skills (written and oral) and collaboration aptitude.
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Demonstrate previous experience in scientific writing and research workflows.
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How to Apply
Interested candidates must submit their online application via the official ETH Job Portal. The application should include:
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A short letter of motivation
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A CV
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Transcripts of Records for both Bachelor’s and Master’s degrees
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Names and email addresses of three referees
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Additional supporting documents (e.g., diplomas, project reports, publications, or thesis).
Benefits
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Full-time, fully funded PhD position (100%)
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Work in a highly stimulating academic environment at ETH Zurich, one of the world’s leading universities
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Access to state-of-the-art research facilities and professional development support
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Public transport season ticket, car sharing options, on-campus sports facilities, childcare support, and attractive pension benefits
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Contribution to a sustainable and inclusive academic culture
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Active participation in the eDIAMOND research project and freedom to develop an individual research profile.
