PhD Position F/M Frugal Distributed Training with Volatile Resources
Inria
Inria is recruiting a PhD researcher to develop frugal distributed-training algorithms for volatile and resource-constrained computing environments.
The current cycle is confirmed, the official application route is active and a closing date is recorded.
Source review was due 24/08/2026. Confirm details on the official page.
Vacancy terms
- Career stage
- Doctoral researcher
- Employment type
- Not stated
- Contract
- Not stated
- Contract ends
- Not stated
- Original contract term
- Fixed-term PhD contract for three years
- Schedule
- Not stated
- Workplace
- Not stated
- FTE
- Not stated
- Salary
- EUR 2,300 gross per month.
- Department or school
- Not stated
- Posted
- Not stated
Responsibilities
- Model volatile resource availability and design distributed-training algorithms.
- Analyse convergence, communication, computation and energy trade-offs and evaluate methods experimentally.
Qualifications and requirements
Qualifications
- Graduate degree or equivalent.
- Solid mathematical background in optimization, probability, stochastic processes or statistical machine learning.
- Good programming skills, preferably Python.
- Fluency in English.
Requirements
- Strong interest in distributed systems and resource-aware machine learning.
- Interest in theoretical analysis and experimental validation.
Documents and steps
Documents
Use the official careers site for the document list.
Steps
Review the distributed-training research objectives.
Prepare the application materials requested by Inria.
Submit online through the official Inria vacancy by 25 October 2026.
Why this vacancy is published
This vacancy was checked against the university's official careers system.
No public evidence excerpt is available yet. Use the linked official source to confirm every material claim.
Published revision history
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PhD Position F/M Frugal Distributed Training with Volatile Resources
Use the enduring programme page to check for a verified newer cycle. A closed vacancy never implies that another round is open.
Programme overview and cycle history