Publisher
source

Inria

Postdoctoral Research Visit in Distributed Machine Learning at the Network Edge Inria in France

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available

Deadline

Oct 11, 2026

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Country

France

University

Inria

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Keywords

Computer Science
Electrical Engineering
Information Technology
Mathematics
Federated Learning
Online Learning
Optimisation
Statistics

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About this position

Inria is advertising a postdoctoral research visit in distributed machine learning at the network edge within the NEO and COATI teams at the Inria Centre at Université Côte d’Azur in Sophia Antipolis, France.

The position is part of the EU-funded dAIEDGE network of excellence on distributed, trustworthy, efficient, and scalable AI at the edge. The research themes include distributed inference, online learning algorithms with regret guarantees, distributed/federated learning, and machine learning privacy.

The postdoc will work with Giovanni Neglia, Chuan Xu, and Frédéric Giroire, and will also collaborate with PhD students in the group. The role includes participation in dAIEDGE activities such as meetings and contribution to project deliverables.

Applicants should hold a PhD or equivalent in Applied Mathematics, Computer Science, or a closely related field. The ideal candidate has a strong mathematical background in optimization, statistical learning, or privacy, plus solid machine learning knowledge and programming skills. Experience with PyTorch or TensorFlow is a plus.

The contract is fixed-term for 1 year and 3 months, renewable, with a gross salary of 2788 EUR/month. Benefits include subsidized meals, partial transport reimbursement, teleworking, flexible hours, leave, training access, and other staff benefits.

Deadline to apply: 2026-10-11. Applications must be submitted online on the Inria website.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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