PhD scholarship in AI-Driven Optimization of Optical Links based on Nano-Lasers - DTU Electro

DTU - Technical University of Denmark; Kongens Lyngby; On-site; DKK 360,000 - 460,000; Full time

Job summary

DTU Electro invites applications for a PhD position on AI-driven optimization of optical links based on nano-lasers, under the POPCOM program and NANOPHOTON center. The project focuses on developing signaling optimization to maximize spectral and energy efficiency while reducing J/bit energy consumption.

The role combines algorithm development with experimental implementation, covering reinforcement learning, physics-informed networks, and data-driven models, with a 3-year appointment and a 30

Qualifications

• Background in fiber optics and laser-physics.
• Experience with machine learning and AI-based optimization.
• Experience applying ML/AI to communication systems and laser modelling is a plus.

Responsibilities

• Develop AI-driven optimization framework for nano-laser-based transmitters and waveforms.
• Realize robust transmitter and receiver architectures for power-efficient signaling at high spectral efficiency.
• Maintain and extend codebase (GitHub) and organize joint experiments with collaboration groups.

Education

Two-year master's degree

Job description

Job Description

DTU Electro invites applications for a PhD position in AI-driven optimization of optical links based on nano-lasers, within the Villum Investigator program "Power-Efficient Fiber-Optic Communication" (POPCOM) and DNRF Center for NanoPhotonics (NANOPHOTON). The position focuses on developing signaling optimization frameworks to maximize spectral and power efficiency.

As data-center traffic continues to grow, the energy consumption of optical links has become a critical bottleneck, with power efficiency (measured in J/bit) increasingly rivaling spectral efficiency as a key performance metric. This project will investigate how AI-driven techniques can jointly optimize nano-laser-based transmitters and their waveforms to reduce energy consumption while sustaining high data rates, contributing to more sustainable next-generation optical communication infrastructure.

Responsibilities And Qualifications

We seek a motivated, curious, and outgoing PhD candidate with a solid background in fiber optics, laser-physics, communication engineering, machine learning, and AI-based agentic frameworks. Experience applying machine learning or AI-based optimization frameworks to communication systems and laser modelling, as well as experimental work, is a plus.

The project goal is to develop an AI-driven optimization framework and apply it to realize robust transmitter and receiver architectures that enable power- efficient signaling at the maximum allowable spectral efficiency. The project will cover both algorithm development and experimental implementation.

We offer an opportunity to develop expertise in various domains, including but not limited to:

• Reinforcement learning for the design of optical links
• Development of nano- laser physical system models and data-driven models
• Realization of experimental procedures for testing the developed frameworks
• Building fiber-optic transmission systems
• Investigating transmission performance in practical test-beds

As a PhD candidate at DTU, you will take part in an educational program of 30 ECTS tailored to your needs, covering technical subjects as well as the "soft skills" needed for a successful career in industry or academia.

Your tasks will include research and development of AI-driven methods for mitigating impairments associated with short-range optical links, using energy-efficient signal processing solutions. The overall goal will be to maximize the information rate given the energy-consumption constraint. Specifically, you will focus on the following areas:

• Gradient-based learning for symbol and pulse shaping
• Model-free reinforcement learning strategies for signal pre-distortion
• Physics-informed neural networks
• Maintenance of the GitHub repository for the developed code
• Organizing and managing joint experiments with collaboration groups

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

Approval and Enrolment

The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.

We offer

DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms

The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. Please see DTU’s salary structure for scientific staff: www.inside.dtu.dk/en/human-resources/during-employment/salary/salary-structures.

The period of employment is 3 years.

Further information

Further information may be obtained from Professor Darko Zibar, [e-mail] and Professor Jesper Mørk [e-mail].

You can read more about career paths at DTU here.

You can read more about DTU Electro at https://electro.dtu.dk/.

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU - Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar "PhD relocation to Denmark and startup "Zoom" seminar" for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position.