PhD Position Data-Driven Techniques for Energy-Efficient and Safe Control of Hydrogen-based Vessels

PhD Position Data-Driven Techniques for Energy-Efficient and Safe Control of Hydrogen-based Vessels

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1 Oct 5 Nov Delft

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Are you passionate about sustainability, clean energy, and technological innovation? Do you have a passion for data analysis and problem-solving? Join us to make a significant contribution!

Job description

With the escalation of global energy demands and growing concerns about climate change, the pursuit of renewable and efficient energy solutions for the shipping industry is intensifying. Among the potential solutions, hydrogen fuel cells have emerged as a promising power source for various vessels, including ships and submarines. However, a barrier to their broader adoption lies in the challenges of achieving energy-efficient operation and safety.

Central to overcoming these challenges is developing control algorithms tailored to the dynamics of hydrogen propulsion systems. Many algorithms have their roots in conventional fuel system designs, necessitating refinements to make them fully compatible with hydrogen-based systems.

Model Predictive Control (MPC) is an advanced control approach that has garnered attention in this context. Its capability to foresee future behaviors and consider system constraints renders it especially useful to hydrogen propulsion systems. This foresight aids in proactive decision-making, ensuring the system’s safety and efficiency. Nevertheless, given the complex nature of hydrogen propulsion systems, significant concerns with MPC are related to the models’ accuracy and computational intensity. However, real-time optimization, especially over extended time horizons, is often computationally taxing.

Artificial Intelligence (AI) and Machine Learning (ML) offer avenues to address these challenges. These techniques can be used to model complex systems and learn from data. Their ability to manage system complexities without explicit modeling makes them invaluable for different systems like hydrogen propulsion. However, there are inherent challenges. First, the nascent state of hydrogen propulsion means there’s limited real operational data available for ML training. Secondly, Deep learning models, in particular, can lack transparency in their decision processes, which raises concerns for safety-critical applications.

To overcome those challenges, this project will focus on developing MPC algorithms for hydrogen-based vessels. To address challenges like model accuracy and computational intensity, you will use ML to develop surrogate models to approximate complex system dynamics, thereby reducing the computational burden of MPC. To ensure that AI/ML models, especially deep learning ones, are interpretable and transparent in their decision-making processes, a focus will be placed on enhancing algorithm interpretability.

You will work in the Sustainable Drive and Energy Systems section at the Maritime and Transport Technology Department. You will be working closely with other researchers working within SH2IPDRIVE and related topics and projects at TU Delft, in close collaboration with the Department of Computer Science of the Università’ Degli Studi di Genova.

You will be part of a team composed of professors, post-docs, and PhD students working on different aspects of sustainability, statistical learning, control, and optimization. You will work at the Delft University of Technology, in the Department of Maritime & Transport Technology, under the supervision and guidance of experts in modeling and simulation of energy systems, statistical learning, and optimization.


Delft University of Technology (TU Delft)


We are seeking an outstanding and enthusiastic PhD candidate who has expertise and/or interest in the data analysis with a focus on maritime applications.

You have obtained, or expect to obtain, an MSc or an equivalent degree very soon related to this area (Data Science, Control Engineering, Computer Engineering or a related field). Mandatory skills include a high proficency of spoken and written English and the capacity to work well in a collaboratory environment.

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.

Conditions of employment

Fixed-term contract: 4 years.

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 € 2770,- per month in the first year to € 3539,- in the fourth year. 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.

For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.


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, Maritime and Materials 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 3mE faculty focusses on fundamental understanding, design, production including application and product improvement, materials, processes and (mechanical) systems.

3mE 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 3mE’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, Maritime and Materials Engineering. Do you want to experience working at our faculty? These videos will introduce you to some of our researchers and their work.


  • PhD
  • Engineering
  • 36—40 hours per week
  • University graduate
  • TUD04467


Delft University of Technology (TU Delft)

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