PhD Position Systems Engineering for Sustainable and Resilient Energy Use in Manufacturing

Job description
Context and Motivation

The industrial sector, including manufacturing, is the third-largest energy consumer in the European Union, accounting for approximately 25% of final energy consumption. As electricity prices rise and new EU-wide sustainability regulations are introduced, such as those addressing energy reporting, emissions transparency, and climate compliance, manufacturers face growing pressure to upgrade infrastructure and improve energy consumption.

To remain competitive and compliant, manufacturers need to understand when, where, and how energy is used, and how it can be optimized for cost savings, sustainability, and operational resilience. However, the path forward is uncertain: What green energy sources are viable? How should infrastructure and operations be reconfigured to meet new sustainability goals? What kind of data and decision support is required?

Research Aim

This PhD project aims to apply systems engineering methodologies to develop an integrated decision-support system for energy-aware and regulation-compliant manufacturing, based on one or more representative industrial use cases.

The successful candidate will be expected to:

• Select and define one or more industrial use cases, including Identification of relevant sustainability requirements and regulations, definition of reconfiguration strategies and KPIs at strategic, tactical, and operational levels.
• Model and analyze key system variables, including change drivers (e.g., regulation, cost, technology) and sources of uncertainty, system architecture and functional interactions using systems engineering tools.
• Design a data infrastructure and monitoring layer that integrates Internal factory-level data, external regulatory and environmental data sources.
• Develop a decision-support framework for real-time and scenario-based energy management, and for strategic and operational planning for energy usage and infrastructure adaptation.

Teaching activities are part of your PhD trajectory and may include, for example: supervising workgroups or lab sessions, assisting in courses, or mentoring BSc and MSc students. While teaching will not be your main responsibility, it offers valuable experience that supports your development and prepares you for future academic or professional roles. Teaching activities will not exceed 20% of your total appointment, averaged over the course of your PhD.

Job requirements
We welcome applications from candidates with a Master’s degree in one or more of the following fields:

• Mechanical Engineering.
• Energy Engineering.
• Industrial and Manufacturing Engineering.
• Systems Engineering or related disciplines.

Desired qualifications and characteristics:

• Solid analytical and systems thinking skills.
• Familiarity with modeling and simulation tools.
• Interest in sustainable manufacturing and energy systems.
• Proactive, curious, and collaborative mindset.
• Willingness to engage with industrial partners and international research networks.

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.

PhD Position Systems Engineering for Sustainable and Resilient Energy Use in Manufacturing

Job description
Context and Motivation

The industrial sector, including manufacturing, is the third-largest energy consumer in the European Union, accounting for approximately 25% of final energy consumption. As electricity prices rise and new EU-wide sustainability regulations are introduced, such as those addressing energy reporting, emissions transparency, and climate compliance, manufacturers face growing pressure to upgrade infrastructure and improve energy consumption.

To remain competitive and compliant, manufacturers need to understand when, where, and how energy is used, and how it can be optimized for cost savings, sustainability, and operational resilience. However, the path forward is uncertain: What green energy sources are viable? How should infrastructure and operations be reconfigured to meet new sustainability goals? What kind of data and decision support is required?

Research Aim

This PhD project aims to apply systems engineering methodologies to develop an integrated decision-support system for energy-aware and regulation-compliant manufacturing, based on one or more representative industrial use cases.

The successful candidate will be expected to:

• Select and define one or more industrial use cases, including Identification of relevant sustainability requirements and regulations, definition of reconfiguration strategies and KPIs at strategic, tactical, and operational levels.
• Model and analyze key system variables, including change drivers (e.g., regulation, cost, technology) and sources of uncertainty, system architecture and functional interactions using systems engineering tools.
• Design a data infrastructure and monitoring layer that integrates Internal factory-level data, external regulatory and environmental data sources.
• Develop a decision-support framework for real-time and scenario-based energy management, and for strategic and operational planning for energy usage and infrastructure adaptation.

Teaching activities are part of your PhD trajectory and may include, for example: supervising workgroups or lab sessions, assisting in courses, or mentoring BSc and MSc students. While teaching will not be your main responsibility, it offers valuable experience that supports your development and prepares you for future academic or professional roles. Teaching activities will not exceed 20% of your total appointment, averaged over the course of your PhD.

Job requirements
We welcome applications from candidates with a Master’s degree in one or more of the following fields:

• Mechanical Engineering.
• Energy Engineering.
• Industrial and Manufacturing Engineering.
• Systems Engineering or related disciplines.

Desired qualifications and characteristics:

• Solid analytical and systems thinking skills.
• Familiarity with modeling and simulation tools.
• Interest in sustainable manufacturing and energy systems.
• Proactive, curious, and collaborative mindset.
• Willingness to engage with industrial partners and international research networks.

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.

PhD Position Direction of Arrival Estimation for Multi-chip Imaging Radar Sensors (DAEMIR)

Job description
Imaging radars are made of several different chips and this introduce inter-chip temperature dependent amplitude and phase variations. Most of the literature deals with calibration of radars assuming a static known condition but these procedures cannot deal with inter-chip variation. This program proposes a systematic study of the limit this variation imposes on the performance of the sensors and techniques to mitigate them by antenna design, algorithm design and the use of information of other sensors available in the car.

Enabling L4-5 Autonomous Driving requires substantial improvement in radar sensor performance in the domain of angular resolution. This translates to the use of large virtual arrays, that are built from multiple modules and dies, each housing several front-ends. Variations among these dies – due to temperature differences, aging, and other factors– introduce time-dependent phase and amplitude errors that reduce angular dynamic range, limiting object separability within the same range-velocity bin. These errors are difficult to calibrate as they are time-variant and need to be reduced during the radar operation with the limited information available.

We would study how to mitigate the effects of inter-die phase and amplitude variation by:

• Designing antenna arrays that reduce the impact of amplitude and phase errors on the DoA estimation performance by means of the placement of the different elements.
• Designing algorithms that estimate and correct for amplitude and phase errors of the array with appropriate algorithms.
• Using information from other sensors – i.e. lidars- to establish a limited number of landmarks that can be used to simplify the calibration algorithm and/or improve the sensor performance.

Radar sensors must operate under tight power and size constraints, so any signal processing algorithm proposed during this program must strike a balance between robust performance and manageable computational complexity.

Milestone/deliverables:

Year 1: Antenna array design to minimize inter-die phase/amplitude errors.

Year 2: DOA calibration algorithms. Define the minimum theoretical error with a set of errors.

Year 3: Complexity reduction of the algorithms by using complementary sensors.

Year 4: Comparison against measurements and final report.

Job requirements

• An MSc degree in an engineering discipline relevant to the PhD research.
• Strong background in linear algebra, signal processing, detection an destimation, and optimization.
• Background in radar and wireless communications is desirable, but not mandatory.
• Experience in programming e.g., Python, MATLAB, R.
• Good verbal and written English skills.
• Excellent communication and interpersonal skills.
• Ability to work in a collaborative environment.

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 of Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

PhD Position Direction of Arrival Estimation for Multi-chip Imaging Radar Sensors (DAEMIR)

Job description
Imaging radars are made of several different chips and this introduce inter-chip temperature dependent amplitude and phase variations. Most of the literature deals with calibration of radars assuming a static known condition but these procedures cannot deal with inter-chip variation. This program proposes a systematic study of the limit this variation imposes on the performance of the sensors and techniques to mitigate them by antenna design, algorithm design and the use of information of other sensors available in the car.

Enabling L4-5 Autonomous Driving requires substantial improvement in radar sensor performance in the domain of angular resolution. This translates to the use of large virtual arrays, that are built from multiple modules and dies, each housing several front-ends. Variations among these dies – due to temperature differences, aging, and other factors– introduce time-dependent phase and amplitude errors that reduce angular dynamic range, limiting object separability within the same range-velocity bin. These errors are difficult to calibrate as they are time-variant and need to be reduced during the radar operation with the limited information available.

We would study how to mitigate the effects of inter-die phase and amplitude variation by:

• Designing antenna arrays that reduce the impact of amplitude and phase errors on the DoA estimation performance by means of the placement of the different elements.
• Designing algorithms that estimate and correct for amplitude and phase errors of the array with appropriate algorithms.
• Using information from other sensors – i.e. lidars- to establish a limited number of landmarks that can be used to simplify the calibration algorithm and/or improve the sensor performance.

Radar sensors must operate under tight power and size constraints, so any signal processing algorithm proposed during this program must strike a balance between robust performance and manageable computational complexity.

Milestone/deliverables:

Year 1: Antenna array design to minimize inter-die phase/amplitude errors.

Year 2: DOA calibration algorithms. Define the minimum theoretical error with a set of errors.

Year 3: Complexity reduction of the algorithms by using complementary sensors.

Year 4: Comparison against measurements and final report.

Job requirements

• An MSc degree in an engineering discipline relevant to the PhD research.
• Strong background in linear algebra, signal processing, detection an destimation, and optimization.
• Background in radar and wireless communications is desirable, but not mandatory.
• Experience in programming e.g., Python, MATLAB, R.
• Good verbal and written English skills.
• Excellent communication and interpersonal skills.
• Ability to work in a collaborative environment.

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 of Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

PhD Position Coupling Sensing to Intracellular Organization in Synthetic Cells

Job description
To sense, a (synthetic) cell needs to dynamically convert an external signal into a change in its internal organization, where the external signal can be a molecule but also a protein displayed on the surface of another synthetic cell. Here, you will experimentally investigate how to optimize the coupling of a transmembrane sensor, which detects an external signal, to a regulatory module, which amplifies this signal into a polarized internal cellular organization, thereby externally setting an axis for cell division or to differentiate cells for synthetic tissues.

You will use various experimental techniques: you will encapsulate the regulatory module in vesicles, integrate signal-sensing components, and analyze the system’s responsiveness through fluorescence microscopy. You will be part of the Laan Lab, and work closely together with the experimental groups of Kristina Ganzinger at AMOLF in Amsterdam and Gijsje Koenderink at the TU Delft, who are all part of EVOLF. EVOLF (evolving life from non-life) is a large, highly collaborative, national consortium, with 31 research groups that together study if, and how, we can create living cells (synthetic cells) from lifeless molecules. You will combine your experimental findings with computer simulations in collaboration with the group of Jos Zwanikken at TU Delft. Your work will enhance understanding of signal-induced polarization in synthetic cells.      

Job requirements
We are looking for an experimentalist, with a background in (bio)physics or quantitative biology, who is eager to combine microscopy, wetlab work and data analysis and has a keen interest in synthetic biology. We are a highly collaborative research group that likes to work on challenging and ambitious problems, that typically combine experiments with computational work. We expect the candidate to be a team-player, to have an independent and well-organized work style, to be communicative and creative, and to contribute to our open, interactive, and social lab culture.

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.

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 Applied Sciences
With more than 1,100 employees, including 150 pioneering principal investigators, as well as a population of about 3,600 passionate students, the Faculty of Applied Sciences is an inspiring scientific ecosystem. Focusing on key enabling technologies, such as quantum- and nanotechnology, photonics, biotechnology, synthetic biology and materials for energy storage and conversion, our faculty aims to provide solutions to important problems of the 21st century. To that end, we educate innovative students in broad Bachelor's and specialist Master's programmes with a strong research component. Our scientists conduct ground-breaking fundamental and applied research in the fields of Life and Health Science & Technology, Nanoscience, Chemical Engineering, Radiation Science & Technology, and Engineering Physics. We are also training the next generation of high school teachers.

Click here to go to the website of the Faculty of Applied Sciences.