PhD Thesis on Adaptive Routing for Quantum Networks
Join a cutting-edge research project in quantum networking.
Best for:Best for candidates with a strong background in quantum computing and machine learning.
Overview
This PhD position focuses on developing a decentralized routing protocol using deep neural networks applied to reinforcement learning for the transmission of q-datagrams in hybrid satellite-terrestrial quantum networks. The goal is to minimize decoherence in quantum memories while maximizing entanglement throughput, leveraging principles of quantum internet through datagrams. The candidate will work at the Institute of Physics in Nice and the I3S laboratory, engaging in both software and network aspects, as well as collecting experimental data to validate results with the INPHYNI team managing the Côte d'Azur quantum network.
What you'll do
- Develop a decentralized routing protocol using deep learning techniques.
- Implement reinforcement learning algorithms for efficient data transmission.
- Conduct experiments to gather data on quantum network performance.
- Collaborate with the INPHYNI team to analyze and validate results.
Requirements
Degree required: Master's degree in Computer Science, Physics, or a related field
Degree offered: PhD
Language: English; proficiency in scientific writing
Instruction: English
- Strong knowledge of quantum computing principles
- Experience with deep learning frameworks
- Familiarity with reinforcement learning techniques
- Ability to conduct experimental research
- Open to all nationalities
- Must hold a relevant Master's degree
Funding & terms
How to apply
Deadline: 2026-10-23
Interested candidates should apply through the provided portal link. Ensure all required documents are submitted before the deadline.
- CV
- Cover letter
- Master's degree transcripts
- Reference letters
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