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PhD Position in Decentralized Resource-Constrained Machine Learning, Switzerland

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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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

  • University or Organization: ETH Zurich

  • Department: Distributed Computing (DISCO) Group

  • Course Level: PhD

  • Award: PhD position (100%)

  • Access Mode: Online

  • Number of Awards: One

  • Nationality: Open to international students

  • The award can be taken in: Switzerland

Eligibility

  • Eligible Countries: All nationalities

  • 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.

  • Admissible Criteria: To be eligible, applicants must:

    • Hold or be about to obtain a Master’s degree in Computer Science, Engineering, Mathematics, or a related field by 1 September 2025.

    • Demonstrate strong academic performance with a solid Transcript of Records.

    • Show theoretical and practical experience in at least one of the following topics:

      • Federated/Deep/Split Learning, Neural Architecture Search, Online Algorithms, Resource-Constrained Networking, Optimization, etc.

    • Have proficiency in Python and experience with PyTorch or similar ML frameworks.

    • Exhibit strong English communication skills (written and oral) and collaboration aptitude.

    • Demonstrate previous experience in scientific writing and research workflows.

How to Apply

Interested candidates must submit their online application via the official ETH Job Portal. The application should include:

  • A short letter of motivation

  • A CV

  • Transcripts of Records for both Bachelor’s and Master’s degrees

  • Names and email addresses of three referees

  • Additional supporting documents (e.g., diplomas, project reports, publications, or thesis).

Benefits

  • Full-time, fully funded PhD position (100%)

  • Work in a highly stimulating academic environment at ETH Zurich, one of the world’s leading universities

  • Access to state-of-the-art research facilities and professional development support

  • Public transport season ticket, car sharing options, on-campus sports facilities, childcare support, and attractive pension benefits

  • Contribution to a sustainable and inclusive academic culture

  • Active participation in the eDIAMOND research project and freedom to develop an individual research profile.

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