PhD Position Holistic Ship Design

Are you passionate about generative artificial intelligence and ships? Join us in innovating the ship design process as we know it. 

Job description

Introduction

Generative AI is transforming how content is created. Whether it is text, images, or music, generative AI can often produce results that match or surpass results created by humans. However, when it comes to engineering design, and specifically naval architecture, generative AI is lagging behind. This is largely due to data scarcity in the maritime domain. Unlike media domains where vast datasets are readily available, ship design data is often proprietary, fragmented, or nonexistent. Despite this, researchers managed to develop generative AI models capable of producing vessel hull designs. Yet, these models face limitations: they often ignore physical constraints, and evaluation of performance and regulatory requirements requires computationally expensive simulations. Moreover, a complete vessel design involves far more than just the hull. It must include internal room arrangements, machinery layouts, cargo compartments, superstructures, ect. All of which must comply with safety regulations, operational requirements, and stakeholder preferences. This PhD position addresses these challenges by developing generative AI models that can produce complete ship designs.

Your responsibilities

To be able to generate preliminary, regulation-compliant ship designs that meet stakeholder requirements, your key tasks will include:

• Data generation, Create training datasets using parametric design and knowledge-based engineering techniques to capture expert knowledge in a reusable format.
• Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model training.
• Generative AI model training, Design and implement generative models such as Generative Adversarial Networks, Variational Autoencoders, and Diffusion Models to generate realistic ship designs.
• Performance assessment, Evaluate generated designs using key performance indicators such as energy efficiency, safety, cost, and emissions to identify optimal vessel configurations.

Research Environment

You will be based at the Maritime and Transport Technology department of the TU Delft, working within an interdisciplinary team led by Dr. Roy de Winter. The team includes PhD candidates focusing on digital twins for sustainable ship design and multi-fidelity design space exploration for wind-assisted ships.

Job requirements 

• We are seeking an enthusiastic PhD candidate who has affinity in the following areas: Generative AI, Ship Design, Design Performance Assessment.
• You have obtained a MSc or an equivalent degree or expect to obtain an MSc very soon, in a related field (Computer Science, Naval Architecture, Marine Engineering, Mathematics, Aerospace Engineering, or other related fields).
• Good spoken and written English and the ability to work in a team are mandatory.

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 Promovendus 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 Dr. Roy de Winter, email: r.dewinter@tudelft.nl.

Application procedure

Are you interested in this vacancy? Please apply no later than 1 November 2025 via the application button and upload the following documents:

• CV.
• Coverletter and names and contacts of at least two references. 

You can address your application to Dr. Roy de Winter.

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.