PhD Candidate in Industrial Internet of Things: The University of Luxembourg is offering a fully funded PhD position focusing on Federated Unlearning for the Industrial Internet of Things (IIoT). This innovative project aims to develop a framework to address challenges in data privacy and compliance while leveraging federated learning methodologies.
PhD Candidate in Federated Unlearning for Industrial Internet of Things
Designation: PhD Candidate (Fixed Term Contract)
| Details | Information |
|---|---|
| Research Area | Federated Unlearning, Industrial Internet of Things |
| Location | Kirchberg Campus, University of Luxembourg |
| Contract Type | Fixed Term Contract (36 Months, extendable to 48 Months) |
| Work Hours | Full Time (40.0 Hours per Week) |
| Internal Title | Doctoral Researcher |
| Job Reference | UOL07008 |
| Yearly Gross Salary | EUR 40,952 (Full Time) |
Eligibility/Qualification:
- MSc degree or equivalent in Telecommunications and Computer Science.
Description:
This position is part of a cutting-edge research initiative aimed at creating a robust framework for federated unlearning in decentralized machine learning systems. The successful candidate will work on challenges including dynamic system adaptation and data privacy within resource-constrained environments. The role involves experimental collaboration within a strong research team led by distinguished faculty members and emphasizes contributions to scientific publications and outreach activities.
How to Apply:
- Prepare the following application materials:
- Full CV including educational background and contact details of at least two recommenders.
- Title and summary of your final thesis.
- List of publications (if applicable).
- Transcript of university-level courses and results.
- Cover letter (500 words) detailing motivations and areas of interest.
- Provide a link to any relevant GitHub repositories (if available).
- Apply through the University of Luxembourg HR system. Applications submitted by email will not be considered.
Last Date to Apply: Early application is highly encouraged as applications will be processed upon receipt.
For further information, you may contact Dr. Ons Aouedi at ons.aouedi@uni.lu.
This scholarship opportunity allows for significant professional and academic growth in a globally recognized research environment poised to lead innovations in secure and intelligent IIoT ecosystems.
