PhD Candidate in AI-Driven Optimization of Optical Links

Job summary

This position involves a PhD scholarship focused on AI-driven optimization of optical links utilizing nano-lasers, as part of a program aimed at enhancing power-efficient fiber-optic communication. The role emphasizes the development of frameworks to improve both spectral and power efficiency in optical communication systems.

Qualifications

• A two-year master's degree (120 ECTS points) or equivalent academic level.
• Background in fiber optics, laser physics, communication engineering, machine learning, and AI-based frameworks.
• Experience with machine learning or AI optimization in communication systems and laser modeling is advantageous.

Responsibilities

• Develop AI-driven optimization frameworks for nano-laser-based transmitters and receivers.
• Conduct research on energy-efficient signal processing solutions for short-range optical links.
• Implement gradient-based learning for symbol and pulse shaping.
• Utilize model-free reinforcement learning for signal pre-distortion.
• Maintain a GitHub repository for developed code and manage collaborative experiments.

Skills

• Proficiency in reinforcement learning and data-driven modeling.
• Ability to design and test fiber-optic transmission systems.
• Familiarity with physics-informed neural networks.

Education

• Candidates must hold a relevant master's degree.

Tools

• Experience with GitHub for code management and collaboration tools for joint experiments.