Post-Doctoral Research Visit F/M Risk Measures in Task-Oriented Communications

TN France; Villeurbanne; Hybride; EUR 40 000 - 70 000; Plein temps

Résumé du poste

An innovative research opportunity awaits in Villeurbanne, focusing on risk measures in task-oriented communications. This postdoctoral position offers a chance to engage in cutting-edge research funded by a national program, collaborating with leading experts in the field. You will explore the intersection of information theory and machine learning, tackling challenges in coding schemes and optimization models. With flexible working conditions, including teleworking options, and a supportive environment for professional growth, this role is perfect for those passionate about advancing communication technologies. Join a vibrant team dedicated to shaping the future of networks!

Prestations

Partial reimbursement of public transport costs

7 weeks of annual leave

10 days RTT

Possibility of teleworking

Access to professional equipment

Participation in social activities

Access to vocational training

Complementary health insurance

Qualifications

• PhD in a relevant field with strong analytical skills.
• Experience in coding schemes and data-dependent optimization.

Responsabilités

• Analyze risk-constrained source and channel coding.
• Develop algorithms for coding with risk constraints.

Connaissances

Information Theory

Machine Learning

Statistical Inference

Optimization Models

Formation

PhD in Computer Science or related field

Outils

Python

MATLAB

Description du poste

Post-Doctoral Research Visit F/M Risk Measures in Task-Oriented Communications, Villeurbanne

Client: INRIA

Location: Villeurbanne, France

Job Category: Other

EU work permit required: Yes

Job Reference: 64531ba5eb7a

Job Views: 1

Posted: 06.05.2025

Expiry Date: 20.06.2025

Job Description:

This postdoctoral research position will be carried out in Inria Lyon, funded by the PEPR Networks of the Future programme. The candidate will be hosted within the MARACAS team in the CITI Laboratory, working primarily with Dr. Malcolm Egan. As part of a national French collaboration, opportunities for interaction with other researchers through seminars, workshops, and short-term visits will be available.

The focus of the PEPR Networks of the Future programme is on fundamental and applied research towards future communication networks, particularly goal-oriented and semantic communications, which tailor communication for specific tasks like training machine learning models or process control. Key aspects include task-dependent constraints such as latency and reliability, and selecting relevant data to communicate.

This position emphasizes coding schemes (compression and channel coding) with guarantees on task performance, focusing on risk constraints that consider the impact of large distortions on task outcomes. The research will involve data-dependent optimization models common in machine learning, statistical inference, and resource allocation.

The main objectives are to design and analyze coding schemes using information theory under risk constraints, where the distortion measure relates to optimality loss in data-dependent optimization. The performance of algorithms for joint source and channel coding will be evaluated against theoretical bounds.

The candidate will also collaborate on federated learning algorithms within the MARACAS project team, participating in seminars, summer schools, and conferences.

Main activities:

1. Information-theoretic analysis of risk-constrained source and channel coding.
2. Development of algorithms for constructing source and channel codes with risk constraints.
3. Simulation-based comparison of theoretical bounds and proposed algorithms.

Technical skills and level required:

Languages:

Relational skills:

Other valued skills:

Advantages:

• Partial reimbursement of public transport costs
• 7 weeks of annual leave + 10 days RTT + potential exceptional leave
• Possibility of teleworking (up to 90 days/year) and flexible hours
• Access to professional equipment (videoconferencing, computers, etc.)
• Participation in social, cultural, and sports activities
• Access to vocational training
• Complementary health insurance under conditions