AI computing with light! Come join us to design and fabricate a unique photonic AI chip that can learn and perform tasks at light speed and high energy efficiency.

Job description

Photonic neural networks offer a promising route toward overcoming the energy and bandwidth limitations of conventional electronic AI hardware. By exploiting interference, parallelism, and the intrinsic speed of light, integrated photonics can execute matrix operations with unprecedented efficiency. This PhD project focuses on developing on-chip photonic neural network architectures that can be trained directly in hardware, eliminating the need for costly off-chip training and enabling scalable, adaptive systems.

You will work at the intersection of nanophotonics, machine learning, and hardware-software co-design to realize robust training mechanisms within programmable photonic circuits. The research combines theoretical modeling, chip design, experimental validation, and algorithm development, contributing to a new generation of sustainable, high-performance AI chips for real-world applications.

Your role:

• Design and model photonic neural network architectures for on-chip implementation.

• Develop in-situ training strategies compatible with analog photonic hardware.

• Fabricate and experimentally characterize novel photonic AI chips.

• Collaborate with interdisciplinary teams spanning nanophotonics and AI.

• Disseminate results through scientific publications, conference presentations, and patents.

What we offer:

• A 4-year fully funded PhD position at TU Delft.

• The opportunity to lead a pioneering project at the intersection of nanophotonics and AI

• Collaboration with international experts from diverse disciplines.

• Access to cutting-edge computational and experimental facilities.

•. Supervision of MSc researchers.

• Mentorship and career development support.

This position is jointly embedded in the research groups of Dr. Sid Kumar and Dr. Richard Norte.
This role involves working across two departments, with shared responsibilities and collaboration.

Research group of Dr. Sid Kumar: https://www.mech-mat.com/

Research group of Dr. Richard Norte: https://www.tudelft.nl/en/me/about/departments/precision-and-microsystems-engineering-pme/people/associate-professors/richard-norte

Job requirements

• Master’s degree in physics, applied physics, nanophotonics, computer science, artificial intelligence, mechanical engineering or related field.

• Experience in nanofabrication.

• Experience with machine learning for scientific applications.

• Experience with programming (e.g. Python, PyTorch, TensorFlow).

• Drive to tackle interdisciplinary challenges and communicate across fields.
• Strong teamwork and communication skills.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Mechanical Engineering

From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to understand our environment and discover its underlying mechanisms, research and education at the ME faculty focusses on fundamental understanding, design, production including application and product improvement, materials, processes and (mechanical) systems.

ME is a dynamic and innovative faculty with high-tech lab facilities and international reach. It’s a large faculty but also versatile, so we can often make unique connections by combining different disciplines. This is reflected in ME’s outstanding, state-of-the-art education, which trains students to become responsible and socially engaged engineers and scientists. We translate our knowledge and insights into solutions to societal issues, contributing to a sustainable society and to the development of prosperity and well-being. That is what unites us in pioneering research, inspiring education and (inter)national cooperation.

Click here to go to the website of the Faculty of Mechanical Engineering. Do you want to experience working at our faculty? These videos will introduce you to some of our researchers and their work.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3059 - €3881 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

Additional information

For more information about this vacancy, please contact Sid Kumar (Sid.Kumar@tudelft.nl) and Richard Norte (R.A.Norte@tudelft.nl).

Application procedure

Are you interested in this vacancy? Please apply no later than 28 May 2026 via the application button and upload the following documents:

• Curriculum vitae (CV)
• Transcript of grades and courses from both your Master's and Bachelor's degrees
• Cover letter describing your interest in and motivation for this position
• A sample of your original scientific writing (e.g., MSc thesis, scientific paper). If your MSc thesis is not yet complete and you do not have a published paper, you may instead provide a project report or other document that demonstrates your scientific writing.

You can address your application to Sid Kumar and Richard Norte.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Please note:

• You can apply online. We will not process applications sent by email and/or post.
• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
• Please do not contact us for unsolicited services.