Delft University of Technology (TU Delft), Netherlands invites online Application for number of Fully Funded PhD Positions at various Departments. We are providing a list of Fully Funded PhD Programs available at Delft University of Technology (TU Delft), Netherlands.
Eligible candidate may Apply as soon as possible.
(01) PhD Positions – Fully Funded
PhD position summary/title: PhD Position on Spatial Planning of Industries Strategies and Circular Economy
Add-reAM aims to foster a sustainable, circular future where waste is minimized, resources are conserved and consumer needs are met without compromising the planet’s health.
While WP1 focusses on the next-generation AM, WP2 designs remanufacturing using AM, WP3 looks into regulatory, economic, political, environmental, and social innovations.
Your research will analyse AM in the Netherlands within geopolitical and socioeconoimc context. The current geopolitical turmoil is increasingly answered with industrial strategies, at EU and NL level, though much is still unclear. A clear ambition is to increase innovation, though after decades of deregulation, no clear industrial strategy, and even the closure of the Ministry of Planning in The Netherlands, a decent understanding, let alone a steering of industry is lacking. Building on earlier research, this PhD project will therefore analyse the structure and dynamics of industrial ecosystems surrounding AM in the Netherlands, examining how firms, institutions, and infrastructures interact to enable—or constrain—the development of a competitive and sustainable AM sector.
Deadline : 7 Dec 2025
(02) PhD Positions- Fully Funded
PhD position summary/title: PhD Position Ceramic Nanofiltration for Water Treatment
Water scarcity and pollution are among the most pressing global challenges. Membrane-based systems are crucial for producing high-quality drinking water, but they also generate concentrate streams rich in emerging contaminants such as PFAS and micropollutants. These streams are often released into the environment, posing risks to both people and ecosystems.
In this PhD project, you will work on the development and optimization of ceramic nanofiltration, integrating advanced materials and innovative water treatment process design to safely manage and minimize these concentrate streams. Your work will contribute directly to the UN Sustainable Development Goals 6 (Clean Water and Sanitation) and 13 (Climate Action), as well as to Horizon Europe Cluster 6 priorities.
In this role you will focus on:
- Modifying ceramic membranes for selective ion rejection from water.
- Conducting water treatment experiments and membrane characterization.
- Collaborating with other PhD researchers and team members to ensure that findings contribute to the shared goals of advancing sustainable water treatment.
Deadline : 19 Dec 2025
View All Fully Funded PhD Positions Click Here
(03) PhD Positions – Fully Funded
PhD position summary/title: PhD Position on Resilient Asphalt Materials under Climate Change
Ensuring the durability and resilience of future road infrastructure requires asphalt materials that can withstand the combined impacts of climate change and traffic loading. The Mechanistic and Data-driven Approach for Developing Resilient Asphalt Materials under Climate Change (MEDAS) project, funded by the Dutch Research Council (NWO), aims to establish a scientific foundation for designing and managing climate-resilient pavements. While current pavement design practices are largely experience-based and successful under moderate conditions, the increasing frequency of extreme weather events introduces new challenges that demand a fundamental understanding of the interaction between materials, environment, and loading.
This PhD research will focus on developing mechanistic and data-driven tools to assess and predict the long-term performance of asphalt mixtures exposed to climate-induced stresses such as temperature fluctuations, moisture variations, and UV radiation. The study will involve both laboratory experiments and numerical modelling, linking climate data and material behaviour across multiple scales. Particular attention will be paid to how environmental factors accelerate damage, affect healing processes, and alter material properties over time.
You will conduct your PhD research within the Pavement Engineering Section of the Faculty of Civil Engineering and Geosciences at TU Delft, where your work will be part of the broader research programme on sustainable and resilient infrastructure materials. The Pavement Engineering Section is internationally recognised for its research in material characterisation, pavement design, and performance modelling. Its research themes include the ageing and healing of asphalt materials, the development of low-temperature and recycled mixtures, rejuvenation and circularity concepts, and the multi-scale modelling of pavement structures. The section’s state-of-the-art experimental and computational facilities support research from chemical and microstructural characterisation (FTIR, DVS, DSC) to full-scale mechanical testing (four-point bending, ITT), as well as advanced numerical simulation.
Deadline : 12 Jan 2026
(04) PhD Positions – Fully Funded
PhD position summary/title: PhD Position on Design and Fabrication of Piezoelectric Resonators for DC/DC Applications
We invite an excellent and highly motivated PhD candidate to join the Microelectronics Department at TU Delft and work on cutting-edge piezoelectric resonator (PR) design and fabrication for next-generation power conversion systems.
This PhD project focuses on the development of high-Q piezoelectric resonators and their co-design with resonant DC/DC converters, enabling ultra-compact, magnet-less, and highly integrated power management solutions. These resonators will play a key role in next-generation compact, high-frequency power converters, enabling magnet-less or highly integrated DC/DC conversion in applications ranging from miniaturised electronics and autonomous sensor/IoT nodes to power-dense subsystems in advanced ICs.
You will explore the full design and fabrication cycle of PR devices, including material selection, device design and optimization, multi-physics (electro-mechanical-thermal) modeling, cleanroom fabrication, experimental characterization and testing. You will also collaborate closely with circuit designers to jointly optimize the PR devices for maximum power transfer efficiency in piezoelectric-resonator-based DC/DC converter architectures (PR-DC/DC).
The work includes finite-element modeling, microfabrication in TU Delft’s state-of-the-art cleanroom facilities (Delft Nano Lab and Else Kooi Lab), and high-frequency characterization using advanced measurement equipment. You will interact with experts in MEMS, materials science, integrated circuits, and system-level power management.
Deadline : 5 Jan 2026
(05) PhD Positions – Fully Funded
PhD position summary/title: PhD Position Algebraic and Topological Dynamics
M(atchbox)-manifolds are natural generalizations of Euclidean manifolds. While the one-dimensional case is relatively well understood, higher-dimensional m-manifolds remain largely unexplored.The focus of your research will be a special class of m-manifolds with additional symmetries that support rich dynamical behavior. These spaces were recently identified as particularly promising: they have now been topologically classified under the assumption of a free abelian group action, which opens the door to applications in higher-dimensional tiling theory and raises new questions on how the abelian condition may be relaxed.
You will collaborate closely with PhD students and postdocs at TU Delft and Leiden University who are working on other aspects of m-manifolds and dynamics. You will join the Applied Probability group at TU Delft, an active research environment spanning a wide variety of pure and applied topics.
Deadline : 31 Jan 2026
Polite Follow-Up Email to Professor : When and How You should Write
Click here to know “How to write a Postdoc Job Application or Email”
(06) PhD Positions- Fully Funded
PhD position summary/title: PhD Position on The Climate Expectation Gap: Perspectives on Future Risks by Households
The successful candidate will work within the SPHINX research team to explore when and how households and firms consider (long-term) climate risks in their economic decisions, such as buying a house or investing in business activities, and how they think about climate adaptation investments. To explore how these decisions depend on people’s expectations about climate physical risks, the candidate will develop theory-grounded questionnaires to be administered across three countries using online surveys. During this 4-year-long project, the PhD student will build on the latest progress in surveys of households and businesses (e.g., regarding risk perceptions, private and public climate adaptation decisions, and traditional expectations measurements), grounded in a range of theories from different social sciences. Synthesizing and extending the knowledge on socio-behavioral factors affecting such long-term (economic) decisions and people’s views on a fair distribution of adaptation funding will be essential here. Most of this PhD project will focus on the statistical analysis of these rich cross-country datasets, also examining whether firms’ decisions differ from households. The goal of this data collection and analysis research is to identify where and how real expectations regarding uncertain climate risks deviate from perfectly rational long-term expectations, and which socio-behavioral biases are most critical in facilitating climate risks to become systemic. This data collection and analysis work will benefit from the computational agent-based and macroeconomic modeling (carried out by other team members).
Deadline : 18 Jan 2026
(07) PhD Positions – Fully Funded
PhD position summary/title: PhD Position Fluid Dynamics of Battery Recycling
The rapid expansion in the use of batteries in recent years has created a critical issue: metals that are necessary for battery manufacturing (cobalt, nickel, lithium, etc) are scarce and their supply is constrained, creating insecurities about future supply and geopolitical frictions. As part of the CRM Lion consortium, TU Delft, in collaboration with several industrial partners, aims to find a solution to the problem by extracting metals from spent lithium ion batteries. The PhD project focuses on multiphase flow simulations to fundamentally understand the fluid mechanics and transport phenomena controlling the metal dissolution and extraction process.
Scientific context: The state of the art method for battery recycling is hydrometallurgical dissolution, also called leaching dissolution. Leaching is a method for metal dissolution and separation that occurs in liquid solvent under mixing conditions. How can this method be optimised to make the process more environmentally friendly and reduce its cost (so that battery recycling can be a valid alternative to conventional mining)? Replying to this question requires an understanding of the convective and diffusive phenomena that occur at the solid-liquid interface of the battery particulate materials during leaching, and how these phenomena affect mass transfer at the level of the particulate suspension.
Project objectives: i) to develop mathematical and numerical models of the coupled fluid and mass transfer that occurs during the process of leaching of the black mass, a particulate (multiphase) mixture that originates from crushed Li-ion batteries, and ii) to investigate the microscale physical processes that give rise to leaching, both in laminar and turbulent flow conditions.
Deadline : 4 Jan 2026
(08) PhD Positions – Fully Funded
PhD position summary/title: PhD Position Inclusive Musculoskeletal Models for Human Movement
Musculoskeletal disorders, affecting muscles, bones, joints, and associated tissues, are the leading cause of disability worldwide. Musculoskeletal models hold great potential for prevention and development of new treatments, but current models often fail to capture sex diversity.
Our NWO Vidi Grant project, “Breaking BIASmechanics”, aims to change this by creating innovative technology for generating accurate musculoskeletal models outside the lab that account for sex variations. In collaboration with societal, industry, and health partners—including NOC*NSF, Vitronic, ModelHealth, and the Sport & Gyn network—these next-generation models will allow us to explore how sex diversity affects movement and musculoskeletal loading, guiding more equitable rehabilitation, prevention, and performance programs.
As a PhD candidate in this project, you will:
- Investigate muscle physiology using advanced techniques such as MRI-DTI, ultrasound imaging, muscle stimulation, and electromyography (EMG).
- Perform anatomical dissections on human specimens to collect in-vitro data for model validation.
- Design and conduct motion capture experiments in diverse settings: laboratory environments, athletic fields, and clinical contexts.
- Collaborate within a team to organize and manage a large-scale human participant study, including recruitment and logistical coordination.
- Communicate effectively with study participants in Dutch.
- Work closely with an interdisciplinary team of experts in biomechanics, anatomy, medical imaging, clinical sciences, and sports coaching.
Deadline : 17 Dec 2025
Click here to know “How to Write an Effective Cover Letter”
(09) PhD Positions – Fully Funded
PhD position summary/title: PhD in N-Dimensional Point Cloud Data Management for Adaptive Meshfree Urban Wind Simulation
Accurate urban wind simulations are vital for understanding microclimate, urban heat, and pollutant dispersion. Yet conventional Computational Fluid Dynamics (CFD) workflows rely on watertight geometric models and volumetric meshes that are slow, complex, and costly to produce. Within the POINT-TWINS project, you will help transform this field by enabling meshfree simulations directly on massive, real-world airborne LiDAR point clouds.
Nationwide LiDAR datasets contain billions of points and are increasingly enriched with additional time and scale dimensions for dynamic, space- and time-adaptive simulations. Managing this n-dimensional data efficiently is a central challenge. In your PhD research, you will explore advanced data structures, Spatial and non-spatial Database Management Systems, and high-performance computing strategies to enable fast, scalable handling of these datasets. You will also investigate deep learning methods for local data augmentation and adaptive point density control, addressing the anisotropy and uneven sampling typical of urban LiDAR.
You will work on a four-year doctoral project jointly supervised by Dr. Azarakhsh Rafiee, Prof. Peter van Oosterom, and Dr. Frits de Prenter. Your home base will be the Department of Architectural Engineering + Technology (Faculty of Architecture and the Built Environment), where you will collaborate closely with a parallel PhD project within the Faculty of Aerospace Engineering focused on meshfree numerical methods. Together, you will work across disciplines to develop the foundations of next-generation urban wind simulation.
Deadline : 31 Jan 2026
(10) PhD Positions – Fully Funded
PhD position summary/title: PhD Position Computational Mathematics: High-Performance Solvers for Indefinite Systems
The Numerical Analysis group within the Delft Institute of Applied Mathematics at TU Delft is offering a full-time PhD position in the area of advanced iterative solvers and preconditioning strategies for large-scale indefinite systems.
Indefinite systems are at the heart of some of the most pressing challenges in modern science and technology. They occur in magnetohydrodynamic (MHD) stability problems for plasma fusion, and in discretized nonlinear Schrödinger equations arising in quantum many-body physics, both giving rise to large indefinite systems that challenge existing solvers.The mathematical and computational hurdles of solving such systems are immense: slow or unstable convergence, lack of robustness, and scalability bottlenecks on modern parallel architectures.
As a PhD researcher, you will be at the frontier of tackling these challenges. The project will focus on mapping and understanding the convergence behavior of methods for indefinite systems, and on translating these insights into effective novel preconditioning and parallelization strategies. The ultimate aim is to deliver solvers that are both theoretically grounded and practically viable for real-world applications.
The PhD will be supervised by Vandana Dwarka in the Numerical Analysis group at TU Delft. The group is internationally recognized for its contributions to iterative methods, numerical linear algebra, and parallel computing. The project will be carried out in close interaction with experts from the Max Planck Institute for Plasma Physics (Garching), the University of Toulouse, and IBM, ensuring strong connections to application domains.
Deadline : 25 Jan 2026
Connect with Us for Latest Job updates
(11) PhD Positions – Fully Funded
PhD position summary/title: PhD Position Data-driven Monitoring for Scale-up of a Biocatalytic Production Process Using UPOs
In this project, you will work on designing a scalable bioprocess using unspecific peroxygenase (UPO) enzymes to produce a panel of synthetically useful chemicals. The envisioned process design will include integrated up- and downstream processing, and you will apply real-time monitoring to achieve in-depth understanding of the bioconversion and accelarate process development time. As a part of the Doctoral Network, you will have the opportunity to participate in workshops and external research stays at partnering institutes/industry to develop technical and transferrable skills.
Deadline : 5 Jan 2026
Polite Follow-Up Email to Professor : When and How You should Write
(12) PhD Positions – Fully Funded
PhD position summary/title: PhD Positions in Explainable and Privacy Preserving AI
AI systems are increasingly used in high-stakes settings such as healthcare where trustworthiness is essential. Today’s explainability methods often do not provide meaningful decision support and, in some cases, can even leak sensitive training data. Models are especially unreliable and privacy-risky when they encounter inputs that were poorly represented in their training data.
Our new project PriXAI, funded through a VIDI grant, aims to solve this.
The project develops techniques that identify when a model is operating in such high-risk regions and uses this information to design new, privacy-preserving learning and explanation methods. Instead of producing generic explanations, PriXAI focuses on generating targeted, privacy-safe evidence that helps users understand when predictions can be trusted.
We are offering two PhD positions that will contribute to this mission. This PhD work is important because it advances the foundations needed for AI systems that are both privacy-secure and reliable in real-world decision-making settings.
PhD Position 1: Explainability for decision support
You will develop explanation and evidence-generation methods that remain stable, informative, and decision-relevant even under privacy noise and limited training support.
An understanding of current explainable AI techniques is highly beneficial.
PhD Position 2: Privacy Preserving Explanations
You will design methods to release model outputs and explanations under rigorously defined privacy guarantees. This includes working with techniques such as differential privacy and PAC-privacy to enable safe model and explanation release.
Familiarity with privacy-preserving machine learning methods is a plus.
Deadline : 11 Jan 2026
(13) PhD Positions – Fully Funded
PhD position summary/title: PhD Position Vibration-Based Quality Monitoring for Metal 3D Printed Samples
Additive Manufacturing (AM), also known as 3D printing, is redefining how we design and produce components – especially in high-tech sectors like aerospace, energy, and mobility. However, ensuring the mechanical reliability and structural integrity of printed metal parts remains a major obstacle for broader industrial adoption. Tiny internal defects, process variability, and complex geometries can make quality assurance slow, expensive, or even impossible with traditional inspection methods.
This PhD project, part of a Dutch Research Council (NWO) Open Technology programme,is a collaboration between TU Delft, the University of Groningen, and Queen Mary University of London. At TU Delft, you will lead the development of a vibrational Non-Destructive Testing (NDT) approach that leverage AI to assess metal parts after the printing process.
In this PhD position you will combine mechanics, data science, AI, and experimental testing. You’ll design and run experiments, write and train algorithms, and contribute to open-source tools that may one day become industry standards. This project offers the freedom to explore fundamental questions, while also building technologies that could transform quality assurance in aerospace-grade 3D printing.
At TU Delft, you will be embedded in a supportive, interdisciplinary team with access to state of the art lab facilities and collaborations across faculties. You will engage regularly with our project partners in Groningen and London, and with industrial stakeholders interested in deploying the methods you develop. Working on campus in Delft, you will make full use of our advanced experimental and lab environment, as this hands on setting means the position cannot be performed remotely.
Deadline : 14 Dec 2025
(14) PhD Positions – Fully Funded
PhD position summary/title: PhD Position in Development of Computational Fluid Dynamics Technique for Pointcloud Geometries
Do you enjoy numerical methods and do you want to pursue a PhD in engineering at TU Delft? The POINT-TWINS project aims to develop novel methods that enable Computational Fluid Dynamics (CFD) simulations directly on point cloud representations of urban environments – eliminating the need for traditional meshing and geometry reconstruction.
Urban wind plays a key role in shaping the microclimate of our cities. You’ve likely experienced how certain building configurations can create wind tunnels, resulting in high-speed gusts. Urbanization and global warming further intensify challenges related to thermal comfort and increase the risk of heat islands. Moreover, urban wind strongly influences air quality, as it governs how emissions and pollutants – such as those from traffic – disperse through cities.
To address these concerns in urban planning and building design, engineers and designers rely on Computational Fluid Dynamics (CFD) simulations to predict how wind patterns will be affected by changes in the built environment. However, traditional CFD workflows require watertight surface models and volumetric meshes – steps that are often labor-intensive, error-prone, and technically demanding. This makes urban wind assessments costly and limits their practical applicability. The POINT-TWINS project aims to overcome these limitations through meshfree simulation. This will open the door to scalable, accurate, and more accessible wind assessments across urban environments.
Deadline : 15 Jan 2026
(15) PhD Positions – Fully Funded
PhD position summary/title: PhD Position Piezoelectric Energy Harvesting from Heavy Mechanical Loads
We are seeking a highly motivated PhD candidate to join our research group in the field of piezoelectric microsystems. The successful candidate will work on the design, modelling, fabrication, and experimental implementation of piezoelectric energy harvesters capable of operating under heavy mechanical loads.
This project aims to develop innovative devices that can convert large-scale mechanical stress into useful electrical energy, enabling autonomous sensors and systems in demanding industrial and structural environments. The research will involve a combination of analytical modelling, multiphysics simulations, device implementation, and experimental validation.
Deadline : 7 Dec 2025
(16) PhD Positions – Fully Funded
PhD position summary/title: PhD Position Code Review Efficiency at the Future of Software Engineering (FUSE) lab
As generative artificial intelligence is transforming the daily work of software engineers, TU Delft and the Meta Dev Infra team join forces in a research lab to investigate how we can leverage AI to advance the daily experience and productivity of software engineers at the scale of Meta’s tens of thousands of software engineers.
Across several tracks, we will develop tools that rethink the future of software engineering. Our work will be informed by sound theories and supported by empirical data. In this project, we will use AI as an opportunity and address the challenges that emerge due to AI. Our goal is to conduct rigorous research, apply our results in practice at Meta and to educate the students of TU Delft about the new insights we gather. We will focus on open science, sharing our results to help developers across the world.
Deadline : 4 Jan 2026
(17) PhD Positions – Fully Funded
PhD position summary/title: PhD Position Predictive Software Testing at the Future of Software Engineering (FUSE) lab
As generative artificial intelligence is transforming the daily work of software engineers, TU Delft and the Meta Dev Infra team join forces in a research lab to investigate how we can leverage AI to advance the daily experience and productivity of software engineers at the scale of Meta’s tens of thousands of software engineers.
Across several tracks, we will develop tools that rethink the future of software engineering. Our work will be informed by sound theories and supported by empirical data. In this project, we will use AI as an opportunity and address the challenges that emerge due to AI. Our goal is to conduct rigorous research, apply our results in practice at Meta and to educate the students of TU Delft about the new insights we gather. We will focus on open science, sharing our results to help developers across the world.
Deadline : 4 Jan 2026
(18) PhD Positions – Fully Funded
PhD position summary/title: PhD Position Engineering Productivity Metrics at the Future of Software Engineering (FUSE) lab
As generative artificial intelligence is transforming the daily work of software engineers, TU Delft and the Meta Dev Infra team join forces in a research lab to investigate how we can leverage AI to advance the daily experience and productivity of software engineers at the scale of Meta’s tens of thousands of software engineers.
Across several tracks, we will develop tools that rethink the future of software engineering. Our work will be informed by sound theories and supported by empirical data. In this project, we will use AI as an opportunity and address the challenges that emerge due to AI. Our goal is to conduct rigorous research, apply our results in practice at Meta and to educate the students of TU Delft about the new insights we gather. We will focus on open science, sharing our results to help developers across the world.
Deadline : 4 Jan 2026
(19) PhD Positions- Fully Funded
PhD position summary/title: PhD Position Automated Code Refactoring at the Future of Software Engineering (FUSE) lab
The focus is on exploring and evaluating the potential of LLM-based automated refactoring of codebases with the ultimate goal of reducing software complexity and improving code quality. We will investigate how LLMs can support and automate tasks such as enhancing maintainability and performance while also reducing technical debt and facilitating bug detection and bug fixing. The main modules include (1) capturing practitioners’ experiences and expectations to establish a roadmap, (2) developing models and benchmarks for LLM-based refactoring, (3) designing autonomous agents, and (4) conducting studies to analyse real-world impact.
We are committed to creating a diverse and inclusive research environment and encourage applications from all qualified candidates, regardless of their background or experience. We believe that diversity contributes to a more innovative and creative research community.
If you do not meet some of the optional requirements listed, we encourage you to still apply and explain how your unique experience and skills can contribute to our research
Deadline : 4 Jan 2026
(20) PhD Positions – Fully Funded
PhD position summary/title: PhD Positions Experimental Fluid Mechanics: Inertial Dense Suspensions
Inertial Dense Suspensions (IDeS) are common in nature and industry, with examples ranging from blood flow and recycling to waste slurry transport, additive manufacturing, and energy storage solutions. Despite their practical importance, these flows remain poorly understood. As a result, even the most basic properties cannot be predicted reliably. For instance, the best available models over- or underestimate the measured pressure drop in a suspension pipe flow by 30–40% across different flow rates. This makes designing and controlling these flows difficult. The difficulty arises partly because these flows do not fit the conventional ‘laminar’ versus ‘turbulent’ classification; they inhabit a terra incognita. Most theoretical studies so far have focused on confined suspensions in the viscous regime, but this idealized approach is insufficient for practical applications. Finite particle size and velocity introduce complex inertial phenomena, such as particle-induced fluctuations, a gradual transition to turbulence, and shear-induced migration. These effects are at best only qualitatively understood, yet they profoundly alter the flow behavior. Understanding and accurately modelling these flows will enable more energy-efficient transport of industrial slurries, improve our understanding of blood flow, and support the development of sustainable manufacturing processes.
Deadline : 4 Jan 2026
(21) PhD Positions – Fully Funded
PhD position summary/title: PhD Position on Integrated Planning of Railway Rolling Stock Circulations and Maintenance
Passenger railway transport plays an essential role in sustainable mobility. It is based on dedicated railway infrastructure, rolling stock and personnel that need to be aligned by efficient planning and replanning to optimize the allocation of the resources and maintain reliable operations in face of disturbances and disruptions. Rolling stock (or railway vehicles) also needs regular maintenance at service locations including inspections, cleaning, and repairs. Incidents during operations such as broken toilets or failing doors may also trigger changes to the plans to prioritize maintenance to these specific train units. The interaction between rolling stock circulations and regular maintenance, including the uncertainties involved, leads to complex logistics problems.
The planning of rolling stock circulations and the regular maintenance at the various service locations is typically done by different planners. In addition, shunting train units between the station platforms and the service locations further complicates the operations (re)planning and involves yet other planners and (shunting) personnel. While regular rolling stock maintenance used to be executed largely in the evening or at night such that all rolling stock is available during the day, saturating capacity at service locations and attractive working hours for personnel require alternative solutions, such as moving rolling stock maintenance to daytime on days or periods with less transport demand.
The objective of this PhD project is to develop and demonstrate a methodology for integrated planning of railway rolling stock circulations, regular maintenance and train unit shunting. The integrated planning offers opportunities such as reduced rolling stock with equal seat availability, more attractive working hours at service locations, and decreased train unit movements for regular maintenance. New innovative approaches need to be developed to schedule rolling stock to timetables and service locations while considering requirements of various personnel and special requests during operations based on specific train unit conditions. This requires multiple-criteria decision-making methods to find effective and efficient integrated planning solutions based on existing tools at Netherlands Railways and newly developed optimization models. Simulation studies will be applied to test and demonstrate the developed concepts and algorithms for integrated (re)planning. This PhD research will use a mixture of techniques from logistics, operations research, multiple-criteria decision making and simulation.
Deadline : 5 Jan 2026
(22) PhD Positions – Fully Funded
PhD position summary/title: PhD Position Image Description via Language Models for Blind and Visually Impaired Readers
As part of a larger research initiative, TACIT (Inclusive Technologies for Access and Social Participation), focused on the co-design of inclusive and accessible AI and XR technologies for people with disabilities. The TU Delft Faculty of Electrical Engineering, Mathematics & Computer Science (EEMCS) invites applications for a PhD position aimed at developing advanced AI-driven image description systems tailored for blind and visually impaired (BVI) readers, addressing the diverse and evolving needs of users with different types and levels of visual and cognitive diversities. Leveraging large language and multimodal models, the research will focus on developing AI technologies to generate informative, concise, and personalized descriptions that enhance accessibility across various contexts. The candidate will engage in identifying user requirements, fine-tuning models for accessibility tasks, and designing mechanisms that automatically adapt image content to individual user profiles. The project also involves close collaboration with BVI individuals and other stakeholders through participatory design and evaluation, ensuring that the solutions are robust not only technically but also grounded in real-world accessibility needs.
We are seeking a highly motivated PhD candidate with a strong interest in artificial intelligence, accessibility, and human-centered design to join the TACIT project. The candidate will work on developing adaptive, AI-driven technologies for people living with blindness and vision impairments. This research will combine technical innovation with inclusive design practices to ensure that the resulting solutions are not only effective but also trusted and adopted by the communities they aim to serve. The ideal candidate is passionate about creating socially impactful technology and eager to engage directly with people with disabilities, caretakers and relevant stakeholders, through co-design and participatory research.
Deadline : 4 Jan 2026
(23) PhD Positions – Fully Funded
PhD position summary/title: PhD Positions in Automatic AMS Test Generation for Advanced Automotive ICs
The Computer Engineering (CE) section of the Quantum & Computer Engineering (QCE) department at TU Delft is seeking two talented and motivated PhD candidates. You will develop industrial-grade test solutions for advanced automotive radar ICs, in close collaboration with NXP Semiconductors, one of the world’s top semiconductor innovators.
This is a unique chance to work on real-world challenges that bridge academia and industry, while helping shape the next generation of reliable automotive electronics.
Deadline : 5 Jan 2026
(24) PhD Positions – Fully Funded
PhD position summary/title: PhD Position Innovative Solar Module Design to Enhance Sustainability and Circularity
In this project, we aim to accelerate the development of novel liquid-filled circular PV modules, which can be repaired and recycled in a modular manner, similar to the Fairphone. The goal of this project is to improve the new PV module design to equivalent or even better performance and durability compared to existing PV modules and, in the process, train a group of young engineers in developing more circular PV modules to spark future innovations .
In parallel, we aim to implement the research findings in a PV start-up company such as Biosphere Solar to introduce the technology to consumers as soon as possible.
List of research goals:
- Experimental comparistion liquid encapsulated PV modules efficiency and repliability on at least on the level of conventional PV modules.
- Demonstrating improved circularity (repairability, remanucaturing, recycling) of liquid encapsulated PV modules.
- Living lab tests of prototypes, providing insights into real life operation conditions to verify energy yield.
Deadline : 11 Jan 2026
About Delft University of Technology (TU Delft), Netherlands –Official Website
Delft University of Technology, also known as TU Delft, is the oldest and largest Dutch public technical university. Located in Delft, Netherlands, it is consistently ranked as one of the best universities in the Netherlands, and as of 2020 it is ranked by QS World University Rankings among the top 15 engineering and technology universities in the world.
With eight faculties and numerous research institutes, it has more than 26,000 students (undergraduate and postgraduate) and 6,000 employees (teaching, research, support and management staff).
The university was established on 8 January 1842 by William II of the Netherlands as a Royal Academy, with the primary purpose of training civil servants for work in the Dutch East Indies. The school expanded its research and education curriculum over time, becoming a polytechnic school in 1864 and an institute of technology (making it a full-fledged university) in 1905. It changed its name to Delft University of Technology in 1986.
Dutch Nobel laureates Jacobus Henricus van ‘t Hoff, Heike Kamerlingh Onnes, and Simon van der Meer have been associated with TU Delft. TU Delft is a member of several university federations, including the IDEA League, CESAER, UNITECH International and 4TU.
Disclaimer: We try to ensure that the information we post on VacancyEdu.com is accurate. However, despite our best efforts, some of the content may contain errors. You can trust us, but please conduct your own checks too.
Related Posts
