PhD Position in Machine Learning: ETH Zurich’s Distributed Computing Group invites applications for a PhD position focused on developing decentralized and distributed data-driven methods for Federated Learning on resource-constrained networks as part of the SNSF Ambizione 2023 project “eDIAMOND.”
PhD Position in Decentralized Resource-Constrained Machine Learning
Designation
PhD Candidate
Research Area
- Machine Learning
- Distributed Systems
- Decentralized Finance
- Theory of Networks
Location
ETH Zurich, Zurich, Switzerland
Eligibility/Qualification
- Excellent Master’s degree in Computer Science, Engineering, Mathematics, or related fields, to be obtained before 1 September 2025.
- Strong Transcript of Records in relevant courses.
- Proficiency in Python and machine learning frameworks (e.g., PyTorch).
- Experience with scientific writing.
- Strong critical thinking and excellent English communication skills.
Bonus Points for:
- Published peer-reviewed articles related to the project.
- Experience with network simulators (e.g., OMNeT++, ns-3).
- Familiarity with High-Performance Computing and Git.
Job Description
The PhD candidate will:
- Design, develop, and evaluate methods and systems for three interconnected research directions:
- Distributing model training and inference over resource-constrained devices.
- Context-aware adaptation of Federated Neural Network architectures based on system resources.
- Communication-efficient knowledge exchange among networked federated large models.
- Follow a scientific research workflow: motivate the problem, identify methodological shortcomings, design and develop systems, execute experiments, and publish findings.
- Participate in periodic meetings for feedback and progress evaluation.
How to Apply
Interested candidates should submit:
- A short letter of motivation outlining interest in the eDIAMOND project.
- CV.
- Transcripts of Records for Bachelor and Master degrees.
- Names and email addresses of three referees.
- Any additional relevant documents (diplomas, theses, published articles).
Note: Applications must be submitted through the ETH Job Portal. Applications via email or postal services will not be considered.
Last Date to Apply
Until position filled
For further inquiries, contact Dr. Antonio Di Maio at adimaio@ethz.ch.
