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Switzerland · Computer Science · Machine Learning Systems
PhD in Reliable Machine Learning Systems
ETH Zurich · Prof. Olivia Keller
Funding: fundedDeadline: 2026-05-30Start: 2026-09-15
The application link is not confirmed yet for this position.
Position overview
Research scalable training and serving infrastructure for reliable foundation-model systems with strong systems guarantees.
Application details
Deadline: 2026-05-30
Funding: funded
Application link: Not confirmed yet
Research themes
ml systemsdistributed systemsreliability
Preparation focus
- distributed systems
- distributed systems fundamentals
- reproducible ML infrastructure case studies
- clear articulation of systems-performance tradeoffs
Advisor and lab signals
Prof. Olivia Keller
olivia.keller@ethz.example- Recent work emphasizes scalable, reliable ML deployment
- Lab blends systems rigor with modern foundation-model infrastructure
Past directions
- distributed training systems
- resource-aware ML serving
Current directions
- reliable foundation-model infrastructure
- evaluation and rollback for production ML systems
How to prepare
- Frame your systems experience in terms of reliability tradeoffs, not only raw speed.
- Show that you can connect ML experimentation with production-grade infrastructure decisions.
Source confidence: 89% · Last checked Mar 31, 2026, 3:15 AM
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