Delft University of Technology (TU Delft), Netherlands invites online Application for number of Fully Funded PhD Degree 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 Degree – Fully Funded
PhD position summary/title: PhD Position in Hydrogen Combustion
The PhD Project focuses on the experimental investigation of hydrogen combustion in sequential combustion systems and combustion in vitiated environments, both of which are often encountered in many applications such as low NOx burners, furnaces, etc. Sequential combustion involves burning fuel in multiple stages rather than in a single combustion chamber. In this process, the hot gases produced in the first combustion stage are then directed to subsequent combustion stages, where additional fuel is injected and burned. This staged configuration allows for better control of combustion parameters, reduces pollutant emissions and offers significant advantages in gas turbine operation.
In the combustion lab at TU Delft, we have already developed an optical accessible staged combustor. The objective of the PhD study is to improve and caliberate this set up and to perform state of the art laser diagnostics for better scientific understanding of the staged combustion process involving hydrogen and other fuels mixtures. The PhD candidate will use the experimental findings to finetune the reaction mechanisms and will combine use the improved reaction kinetics mechanisms to identify the main pollution forming pathways. This improved knowledge should then be translated into design rules for staged combustion of hydrogen or hydrogen rich fuels.
Deadline : 30 March 2025
(02) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Smart Agent-based Modelling Meets Green Steel System Change
The Dutch steel sector involves many stakeholders with different goals, including steel producers, recyclers, the government, employees, and local communities. Their interactions create a complex system that is difficult to understand. However, understanding this complexity is essential for identifying policies and actions that promote positive collaboration among them. To achieve this, the PhD project will develop customized agent-based models using reinforcement learning. These models will help map out agent interactions and provide a digital platform for exploring policies that enhance stakeholder relationships at both the system and value-chain levels.
This PhD position is part of the Groeien met Groen Staal national program. The Groein met Groen Staal program is the enabler of a revolution in green steel production at national and international arenas. It will develop solutions to overcome technical, economic and societal bottlenecks towards the following overarching goals: i) Make Dutch steel sector a leader in sustainable steel; ii) Quadrupling of scrap sorting activities; iii) Tripling of steel reuse and remanufacturing activities; iv) Reduce dependence on foreign steel/iron ore through scrap recycling; v) Reduce industry CO2 emissions by 30% and reduce other emissions (including nitrogen oxides and particulate matter) by 50%. The project contributes to reaching this overarching objective by enabling: i) More informed decision, by policymakers and industry leaders, regarding the regulation, support, and promotion of green steel; ii) Understanding of the possible impacts of different policies on the interactions between stakeholders in green steel; iii) Establishing novel methodological best practices (methods and benchmarks) to model system change at the context and value-chain level.
Deadline : 16 March 2025
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(03) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Advanced Numerical Analysis for Probabilistic Assessment of Masonry Infrastructure
We are looking for a PhD candidate to work on advanced numerical analysis and improve the assessment of historical infrastructure, specifically masonry quay walls, which are a specific type of earth-retaining structure. This infrastructure plays a key dual role in many historic cities, especially in the Netherlands, serving both as functional infrastructure and as culturally significant assets. Originally designed as gravity retaining walls, quay walls are increasingly exposed to higher loads due to vehicle traffic on carriageways above their backfill. Additionally, many historical quay walls suffer from material degradation, particularly in timber foundations, making accurate assessment essential. However, traditional methods often result in conservative predictions, and the absence of standardised procedures for evaluating multi-wythe masonry walls adds to the complexity.
Deadline : 14 March 2025
(04) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Computational breeding for potato performance and resilience
The PhD candidate will study the available physiology-informed and data-based potato crop growth models and identify major genotype-specific parameters that control the performance and resilience of crop traits, such as tuber yield and quality traits with respect to drought and Nitrogen-deficiency. Next, the candidate will construct a predictive hybrid model by (a) retrieving estimates for performance and resilience-defining parameters from experimental time-series data about canopy and tuber yield for a diversity panel of potato cultivars and (b) model the genotype-specific growth parameters as functions of molecular marker profiles. This research is on the intersection of dynamic crop growth models and genomic prediction and may involve mathematical disciplines as ordinary differential equations, continuous optimization, ill-posed problems, linear and nonlinear mixed-effect models, overparameterized regression, Bayesian models and regularization. On the biological side, some knowledge of crop physiology, plant breeding and quantitative genetics will be useful.
Deadline : April 20, 2025
(05) PhD Degree – Fully Funded
PhD position summary/title: 2 PhD Positions Find2Fix: Reducing Software Errors using Transparant AI
You will research the state-of-the-art in AI and apply it to real-world software problems at our industrial partners: ASML and DCODIS (a start-up). This is technically challenging applied research with as main outcome a proof-of-concept tool that allows developers to quickly find and fix software errors including security vulnerabilities. You will innovate the Find2Fix pipeline by making the different steps, including found issues and suggested patches, easier to understand using interpretable AI using state machine models and LLM-based explanations. You will provide the community with the first tool for self-healing software that is useful for research, education, and industrial use. Your research will be published and presented at international AI, software engineering, and security venues.
Deadline : 30 March 2025
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(06) PhD Degree – Fully Funded
PhD position summary/title: Phd Optimizing Deep Learning Models for Low Power MCUs.
You will be part of a team investigating a system that monitors a given area in a privacy-preserving manner (without using cameras).
Monitoring is central to the efficient and safe operation of smart homes, buildings, and cities. For example, monitoring systems may need to report an intruder breaking into a house or request help for an elderly person living alone who has fallen.
The challenge is that most monitoring systems rely on cameras, and citizens are becoming increasingly concerned about their abuse by governments or corporations. Together with a leading Dutch company, Signify, we aim to investigate monitoring platforms that cannot provide personalized information, even if they are hacked.
To achieve our goal, we are investigating platforms at the intersection of deep learning and embedded systems. We want to develop a system that is accurate but works with limited computational and energy resources.
Deadline : 30 March 2025
(07) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Metabolic Efficiency in Mammalian Cell Culture
Are you an MSc graduate eager to make a meaningful impact in mammalian cell metabolism and bioprocessing? Do you want to conduct research at the intersection of fundamental and applied science within a multidisciplinary and international team? We offer an exciting PhD opportunity focused on the oxygen-dependent physiology of cultured mammalian cells in suspension, with direct industrial relevance.
Cultured mammalian cells are essential to various industries, from antibody production to the promising field of cultivated meat. Their energy metabolism is a key determinant of production efficiency, and oxygen availability plays a critical role in energy conversion and growth. This project aims to quantify the impact of oxygen on mammalian cell metabolism, bridging 2D cultures to continuous (3D) bioprocesses, and integrating advanced metabolic measurements. By quantifying the role of oxygen in cell physiology and optimising mitochondrial metabolism, we seek to enhance process efficiency and unlock industrial applications.
Deadline : 4 March 2025
(08) PhD Degree – Fully Funded
PhD position summary/title: PhD Position in Quantum Networks
The vision of a Quantum Internet is to provide fundamentally new internet technology by enabling quantum communication between any two points on earth. Such a Quantum Internet will – in synergy with the ‘classical’ Internet that we have today – connect quantum processors in order to achieve unparalleled capabilities that are provably impossible using only classical communication.
Three PhD positions are available on the topic of quantum network applications and quantum network systems in the group of Prof. Dr. Stephanie Wehner at Delft University of Technology (QuTech and Quantum Computer Science):
1. Quantum Network Applications from Non-local correlations: The goal of this position is to determine possible applications and use cases for quantum networks derived from non-local correlations obtained by measuring entanglement. Examples exist that show that non-local correlations can improve coordination tasks, for example in load balancing, distributed control, or graph coordination problems. In this position we will explore new application domains and/or develop a general understanding of domains in which existing examples highlight potential benefits of exploiting non-local correlations generated by entanglement. This project could depending on the interests of the candidate, either take on a more use case oriented direction in collaboration with potential end users, or focus more on a general theoretical understanding of this application domain. For this position, the successful candidate has a strong background in quantum information and/or one of the example domains mentioned above.
2. Quantum Network Applications for Users: The goal of this position is develop real world use cases for quantum networks, in collaboration with an end user. The type of application and use cases of interest in this case is strongly directed by the interests of the end user. The successful candidate has a background in quantum information, and should be highly motivated by the opportunity of developing real world use cases in collaboration with others with the potential to lead to later proof of concept demonstrations.
3. Quantum Network Systems for a Prototype network: The goal of this position is to further optimize the software and network stack developed by our group for execution on the Quantum Internet Alliance prototype network. The successful candidate should be strongly motivated by the desire to design and build real-world quantum network software systems in a large collaboration, and enjoys experimenting with different approaches to optimize engineering goals. The successful candidate has a background in computer science, computer engineering or related fields, with a demonstrated interest in applied systems research.
Deadline : 23 March 2025
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(09) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Musculoskeletal Researcher of Soft Tissue Contributions to Knee/Implant Performance
We are seeking a PhD researcher for a 4-year contract to advance computational models of the human knee based on MRI imaging and robot sensing and manipulation. The aim is to evaluate knee joint laxity pre- and post-operatively through model-based estimates and kinematic and force measurements from a collaborative robot. By understanding the soft-tissue mechanisms at play in the knee we can use models to inform and optimize physical therapy and surgical planning. You will design healthy-subject and cadaver experimental studies with instrumented implants to test and validate model-based estimates of soft-tissue loading. Together with a fellow PhD in robotics, you will develop subject-specific tissue loading maps that describe how the structures in the knee are loaded during robot-assisted therapeutic exercises and gait.
Deadline : 23 March 2025
(10) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Benchmark Model Tests and Performance Assessment of Appendages for Wind-assisted Ships
The growing urgency to decarbonize the shipping industry has led to renewed interest in wind-assisted propulsion as a viable means to reduce fuel consumption and emissions. However, accurately predicting the performance of wind-assisted ships remains a challenge, requiring validation of advanced simulations with high-quality experiments.
Computational Fluid Dynamics (CFD) is increasingly used to predict the performance and forces acting on wind-assisted vessels, but experimental validation remains essential, particularly in complex hydrodynamic scenarios. This PhD position focuses on performing towing tank experiments and high-fidelity flow field measurements using Particle Image Velocimetry (PIV) to validate CFD models.
Beyond validation, these experiments will also assess the effectiveness of different auxiliary appendages in maintaining yaw stability. Combined with high-fidelity flow measurements, this will provide crucial insights into the flow dynamics and performance of various appendage configurations on model scale. Findings from model tests should be ultimately translated to full-scale performance through simulations with the validated numerical tools.
Deadline : 31 March 2025
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(11) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Mechanosensing ion Channels in Artificial Lipid Bilayers Formed in Microfluidic Devices
Would you like to monitor the activity of single mechanosensitive membrane channels being inserted into artificial cell membranes? This will be the focus of a PhD project that will use new microfluidics tools combined with cell-free protein synthesis. A microfluidics system with freestanding lipid bilayers will enable the electrical monitoring of ion channels while a mechanical load is directly applied. The knowledge generated by this project will contribute to making synthetic cells which are responsive to the environment. The general goal is to advance (mechano)sensing in synthetic cells through optimization of ion channels incorporation and activity in lipid bilayers. The project sits at the interface of microfluidics, physics and biochemistry. The PhD student will be part of an interdisciplinary very active consortium called EVOLF.
Deadline : 25 March 2025
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(12) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Generative AI for Aviation Operations
Generative AI is revolutionizing various industries, including aviation. In the context of flight operations, Generative AI holds the potential to transform how we approach critical tasks such as trajectory generation, air traffic control, and weather prediction. By leveraging advanced AI techniques, aviation can achieve new levels of efficiency and safety.
The VITOLMINS project is at the forefront of this transformation, focusing on enhancing the operations of electric Vertical Take-Off and Landing (eVTOL) aircraft. The project aims to integrate eVTOLs into existing air traffic systems seamlessly, utilizing European Global Navigation Satellite Systems (EGNSS) and Copernicus services. This integration is crucial for optimizing air traffic flow and ensuring that eVTOL operations do not interfere with traditional aircraft, thereby maximizing airport capacity and operational efficiency.
Within this framework, the PhD project will explore the application of Generative AI across three key areas: trajectory generation, air traffic control, and potentaillly weather models for aviation. The candidate will have the opportunity to develop and apply cutting-edge machine learning models for real-world aviation challenges, contributing to both the theoretical advancement of Generative AI and its practical implementation in aviation.
Deadline : 15 March 2025
(13) PhD Degree – Fully Funded
PhD position summary/title: PhD Position in Probability Theory and Geometry
The voter model is a stochastic process describing how individuals adopt opinions from their neighbours in a network. In this project, you will define and study the voter model in the geometric context of Riemannian manifolds. As networks we will use random graphs approximating Riemannian manifolds. The main goal is to investigate how geometric properties affect the behaviour of the voter model. You can for instance think about the time it takes to reach consensus, or correlations between opinions of different individuals.
This project is part of a larger aim to study connections between probability theory and (differential) geometry. In the Applied Probability group at TU Delft, we have various research projects on this theme, giving you great opportunities for further collaborations on this topic.
Deadline : April 6, 2024
(14) PhD Degree – Fully Funded
PhD position summary/title: PhD Position 3D Reconstruction and Modelling of Roofs in European Cities
The overall goal of this fully-funded PhD position is to support the researchers and practitioners in the project “MultiRoofs” by designing and implementing algorithms for the 3D reconstruction of buildings and for the classification of roofs. MultiRoofs (Multifunctional Roofscapes for smart, green and just urban densification) is an EU-project that aims to enable public authorities to increase the multifunctional use of rooftops in their urban areas. The project is composed of 25+ industry and academic partners in Western Europe (including Rotterdam, Paris, Dublin, Brussels) and it is an extension of a prototype developed in Rotterdam, the Netherlands by MVRDV.
Deadline : 2 March 2025
(15) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Quantum Optomechanics
Quantum physics has revolutionised the way we live—just think of the billions of transistors working to enable you to read this advert. But its phenomena only dominate at the “small” scale of atoms and molecules. Imagine being able to extend effects like quantum superposition or entanglement to “big” objects that we usually think of as classical particles. This is exactly what you will do at TU Delft. As a PhD student in Quantum Levitodynamics, you will explore how solid bodies, containing billions of atoms, can be made to behave like quantum systems, using techniques such as optical levitation, interferometry and active cooling to control their motion.
You will conduct research on how quantum effects can be exploited for nano and microparticles, building on our recent results. Levitation in vacuum allows the study of quantum-mechanical motion of macroscopic bodies, providing a way to explore the classical-quantum boundary at unprecedented mass and length scales. Combined with the quantum-limited measurement capabilities of optical interferometers, state estimation protocols and ultra-high vacuum engineering, such systems become extremely sensitive probes for a wide range of phenomena, including collisions, fictitious forces and gravitational fields to name but a few. Building on this framework, we have recently developed methods to manipulate the motion of levitated nanoparticles with a precision far better than its zero-point motion (ZPM). In this role, you will explore alternative quantum measurement schemes to prepare exotic quantum states. You will also help us bridge the gap with the macroscopic world and explore potential applications of such systems.
Deadline : 28 March 2025
(16) PhD Degree – Fully Funded
PhD position summary/title: PhD Position in Chemistry and Chemical Engineering for (photo)Electrochemical Synthesis
This research aims to develop new sustainable chemical pathways for the post-fossil chemical industry. In this lab, we explore chemical approaches to challenges encountered in the transition towards a sustainable society and circular economy. Inspired by how nature solves problems, we use biomimetic concepts applied in (photo)electrochemistry and photocatalysis for the generation of specialty chemicals. Specifically, the PhD candidate will develop supramolecular and bio-inspired materials to convert simple building blocks into complex molecules in (photo)electrochemical cells. The start of the project has a strong focus on molecular synthesis, followed by integration of the materials onto electrodes for device fabrication for (photo)electrochemical catalysis. This research pushes artificial photosynthesis towards the light driven generation of solar chemicals in devices by combining synthesis of materials, electrode preparation, electrochemical characterization and mechanistic studies using different spectroscopic methods.
Deadline : 11 March 2025
(17) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Optical Metrology
This exciting PhD opportunity is both experimental and computational. It entails a range of fundamental problems in optics. One of them is to determine a spatially-dependent refractive index distribution of an unknown sample, akin to a “tomogrophy” of the refractive index. This represents a crucial step towards freeform gradient-index optics. The latter offers novel optical design perspectives towards tailored refractive indices employing inverse design.
The PhD is embedded in the AWAVE project and offers a multidisciplinary approach interfacing with a large team both locally at TU Delft as well as Eindhoven University of Technology and University of Twente as well as industrial partners. Thus, a platform that represents a diverse and internationally attractive training ground.
Deadline : 23 March 2025
(18) PhD Degree – Fully Funded
PhD position summary/title: PhD position Safe Use of AI in Telecommunication Networks, NExTWORKx
Telecommunication networks are becoming increasingly programmable and automated. Various types of software can now be integrated to operate these networks in the cloud. While this enhances performance, for example through the use of AI-based algorithms, it also raises important questions about security and reliability. How can we use network modeling to ensure these technologies are operated safely and efficiently?
Scientific challenges for this exciting PhD project include: how to model the various interdependencies between hardware and software components, using network modelling; how to assess the safety of such interconnected critical infrastructure and how to design and implement efficient algorithmic implementations of the theoretical models.
You will be supervised by Dr. Caterina De Bacco from the Network Architecture and Services Group and Dr. Eric Smeitink from KPN, working closely with a collaborative team.
Deadline : March 30, 2025
(19) PhD Degree – Fully Funded
PhD position summary/title: PhD Researcher to Investigate Single-Cell Biophysics in Early Metastasis
Mac4Me (Macrophage Targets for Metastatic Treatment) is a pan-European Marie Skłodowska-Curie Doctoral Network (DC) with 18 PhD candidates aimed at understanding the specific tumour cell-immune host interactions at the metastatic site to identify new immune targets. Mac4Me will use animal-free organ-on-chip (OoC) systems to recapitulate early liver, bone and brain metastasis of cancer developing across our life, such as neuroblastoma, breast and prostate cancer. Data from these preclinical models will be integrated with real-world clinical data using AI approaches to identify new immune targets. Mac4Me offers a unique and innovative research training programme comprising both scientific knowledge and transferable skills and integrating participatory science principles as a starting point.
At TU Delft you will focus on investigating the biophysics of single cells in early cancer metastatic conditions. The goal is to quantify shape, size, mechanical properties and adhesion strength of individual cancer and immune cells to discover potential biophysical disease markers. Experiments will be performed using AFM and FluidFM methods on the available advanced bioAFM instrument. A novel patented multifunctional microfluidic AFM probe will be used to perform efficient integrated measurements. Suitable analytical models will be developed to analyze the data and interpret the results in collaboration with other partners in the network. Analytical frameworks like RHEOS software, FEM models and machine learning concepts for large data sets generated will be explored with collaborators.
Deadline : 16 March 2025
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(20) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Digitally Modulated Radar
Constantly evolving advanced driver assistance systems (ADAS) demand radar sensors with classification capabilities of detected objects. However a drastic increase of number of automotive radars on the street creates their mutual interference. The goal of this project is to develop new class of sensing waveforms to be used by MIMO radars operating in a very dense electromagnetic spectrum. These waveforms should be separable in a low complexity digital receiver, which should be developed as well. The ambiguity function of the waveform should have low level of sidelobes in the range, Doppler and angular domains. The digital code and the carrier should be adjustable to the properties of the electromagnetic spectrum at the moment of transmission. The intelligent aspect of the waveform will enable the radar to adapt its parameters and processing to the changes in objects’ properties and environment (both clutter and interference). New sensing signals should be realizable within the analogue bandwidth of available ADC circuits. The performance of the waveforms and the digital receiver should be verified experimentally. Dedicated measurement set-up has to be developed as a part of PhD duties.
Deadline : 15 March 2025
(21) PhD Degree – Fully Funded
PhD position summary/title: PhD Machine Learning for Energy System State Estimation
TU Delft is a top-tier university and is exceedingly active in the field of Artificial Intelligence (AI) with a strong expertise in energy systems. Energy systems are the backbone of our modern society but are becoming increasingly complex and challenging to operate as renewable energy, heating and transport sectors are integrated into the system. It’s crucially important that energy systems are sustainable, reliable and effective, now and in the future.
As part of your 4-year PhD project, you will develop novel graph-based machine learning algorithms for state estimation of energy systems. The scientific challenge is to design a real-time state estimator for an active distribution system considering topological uncertainties. State estimation is an important task where the operator considers very little noisy measurement data to infer the full system state. However, often, the accuracy is used to infer the full state while the true state is seldom known and can only be reproduced in computer simulations. Therefore, you will explore a novel approach investigating graph neural networks and structural information combining with parameter estimation methods. Your PhD research will be in the area of applied data-driven scientific computing combining statistics, time-frequency analysis, low-dimensional model reductions, and other techniques to extract information from data. You will apply self-supervised learning making the information useful for the management and planning of complex energy systems considering foundational models.
Deadline : 31 March 2025
(22) PhD Degree – Fully Funded
PhD position summary/title: PhD position Cryo-CMOS Circuit Design of Temperature Sensors for Quantum Computers
In this project, you will address the crucial challenge of thermal management in a cryogenic system. Quantum system requires complex integration strategies, often involving 3D integration of multiple chips and components. Sensitive elements, such as quantum bits (qubits), can heavily suffer from temperature variations and must be kept at the lowest possible temperature. Other elements, such as the cryo-CMOS electrical interface, can dissipate significant power, but thermal crosstalk to other system parts must be minimized. Any thermal management strategy would require accurate sensing of the temperature of the different parts, but existing cryogenic temperature sensors are bulky, expensive, and require an accurate analog readout and extensive calibration. To circumvent this limitation, your research will target the invention and development of a fully integrated smart temperature sensor operating at cryogenic temperatures as low as 4 K and below. Although smart temperature sensors in CMOS technology have been developed for decades over the standard temperature range around room temperature, those standard techniques cannot be readily applied at cryogenic temperatures, thus requiring innovations in terms of sensing elements, readout circuitry, and power efficiency. Over the course of your PhD, you will design several prototypes of cryo-CMOS temperature sensors, tape them out in advanced CMOS technologies, and characterize the resulting prototypes in our advanced cryogenic electrical characterization laboratory.
Deadline :30 March 2025
(23) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Cryo-CMOS Circuit Design for Optical Communication in Quantum Computers
In this project, you will address a crucial challenge in quantum computers: how to efficiently transfer a large amount of digital data in and out of a cryogenic refrigerator? The quantum processor will operate in a closed chamber cryogenically refrigerated, thus requiring the transfer of both the input data and the computation results in and out of such a cryogenic chamber over a distance of up to a few meters. While electrical communication via conducting wires seems the straightforward solution, this approach suffers from several limitations, including generating electromagnetic interference and the limited data bandwidth of electrical interconnects. Furthermore, electrical conductors also conduct heat, thus occupying part of the cooling budget of the cryogenic refrigerator. Optical communication presents then a promising alternative thanks to the low thermal conductance of optical fibers and the excellent performance in terms of interference and data rate. Your research will aim to demonstrate the first cryo-CMOS optical transceiver. You will identify the best optical-electrical transducer to operate at cryogenic temperatures and design the cryo-CMOS electric interface to transmit and receive high-speed digital data. Over the course of your PhD, you will design several prototypes of the different cryo-CMOS components of the optical transceiver, tape them out in advanced CMOS technologies, and characterize the resulting prototypes in our advanced cryogenic electrical characterization laboratory.
Deadline : 30 March 2025
(24) PhD Degree – Fully Funded
PhD position summary/title: PhD ROBAHS: Robust Ammonia and Humidity Sensor
Ammonia is recognised as a poisonous gas which is also highly corrosive. Humidity, although not corrosive, is difficult to measure reliably in the long term. Silicon carbide is an extremely robust material and able to withstand these harsh environments for the long term. Temperature sensing is also important for many applications and a temperature sensor will be added. Porous silicon carbide has been shown to be able to measure both ammonia and humidity with high reliability. However, the materials need to be optimised and developed into a compact and reliable sensor system.
As a PhD student at the faculty of EWI of TU Delft you will develop a robust ammonia/humidity sensor based on porous silicon carbide. This involves devopment and optimisation of the basic material, better understanding of the sensing mechanism, processing in de EKL cleanroom and measurement. Measurement will be performed in our laboratories and also in the field.
Deadline : March 30, 2025
(25) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Battery Energy Storage for Multi-functional Traction Grids
Energy storage for the sake of braking energy recuperation and release will probably never have a solid business case. The often overlooked benefits of energy storage are voltage control and peak shaving when the traction grid has renewables and third-party users (houses, EV chargers, etc.) connected to it. This multi-functional use of a traction grid is an urgent necessity in times of grid congestion. Still, how do we properly size the RES system when it is connected to the DC side and faces a significant generational mismatch? How do the connected EV chargers maximize their consumption of the excess RES and braking energy generation? How can battery energy storage, at the heart of this operation, properly buffer these connected sources and loads, and how can we build a robust state estimator, with the very few available measurements, to still allow it to properly dispatch? Finally, we must design a suitable, wide-input range, wide-output range, multi-port converter to connect the Batteries, EV chargers, RES, and the traction grid together.
Deadline : 30 march 2025
(26) PhD Degree – Fully Funded
PhD position summary/title: PhD in Design, Operation & Management of Wastewater Transport Systems & Urban Drainage Transitions
Wastewater transport systems, comprising pumping stations and transport mains, are key components of the urban water infrastructure. Wastewater transport systems have a long (design) service life, while both the upstream sewer systems and the downstream wwtp’s change and evolve over time introducing new failure mechanisms. E.g. the introduction of blue green infrastructures result in a changed hydraulic loading, while RTC and optimisation of wwtp’s introduce changes in the day to day operation which may result in higher sedimentation or H2S degradation rates. Moreover, for decades the Dutch water boards assumed a zero growth in population, while over the last decade both the Dutch population and the urban area have increased strongly. All of this warrants the development of new design strategies that incoporate aspects such as redundancy, flexibility and adaptability.
This PhD position focuses on the development of novel design and maintenance strategies for wastewater transport systems that are able to deal with foreseen and unforeseen transitions in the upstream and downstream infrastructures. This research is part of the knowledge programme Urban Drainage funded by the Dutch urban drainage sector. The Urban Drainage programme is part of the Sanitary Engineering section of the department of Water Management at the faculty of Civil Engineering and Geosciences of TU Delft.
Deadline : 7 April 2025
(27) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Robust Selection of Top-Level Requirements for Future Sustainable Aircraft
The goals for future aviation are ambitious. On a global scale, air traffic is expected to continue growing in the foreseeable future. At the same time, reducing the climate impact of the aviation industry is an urgent challenge. To achieve this, aircraft concepts are being explored that utilize novel energy carriers such as batteries and hydrogen. These novel powertrains impact flight performance, aircraft capabilities, and overall airline operations. Despite these challenges, such technologies must find the correct market position in multi-fuel fleet operations, ideally from their first introduction.
As a PhD candidate at TU Delft, your key challenge will be to develop models and tools to determine the optimal aircraft top-level requirements that facilitate the integration and widespread adoption of sustainable technologies, considering their practical constraints and future potential.
In this research project, the following three aspects will be considered:
- The research will leverage and extend existing open-source air traffic data as input for strategic fleet planning and top-level requirement selection.
- Looking into the future of aviation involves many uncertainties. Therefore, we seek an approach that leads to robust solutions under different future scenarios.
- Flight performance and operational constraints of hydrogen and (hybrid-)electric aircraft must be taken into account.
Deadline :14 March 2025
(28) PhD Degree – Fully Funded
PhD position summary/title: PhD Position on Cryogenic Low-Noise Low-Power Sub-10GHz Receivers
In this Ph.D. research, we will focus on the development of cryogenic CMOS receivers with 4K noise temperature. We will first investigate the essential functionalities required to read out the multiple resonators and compare different readout architectures based on their potential in scalability, intrinsic signal-to-noise ratio, and shortest readout time. Then, the impact of the circuit nonidealities, such as noise and distortion, on the readout fidelity is investigated. Based on this study, the system-level specifications for readout electronics will be quantified. We will review the characteristics and behavior of CMOS active and passive components at cryogenic temperatures. While keeping the device characteristics and required specs in mind, the block diagram and circuit schematic, including low-noise amplifiers, mixers, and baseband amplifiers, will be designed and measured.
Deadline : 23 March 2025
(29) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Extended Target Tracking & Classification with Phased Array Radar
Climate change is a pressing issue that can drastically affect the ecosystem. Understanding the changes in weather in different parts of the globe is one of the significant steps that should be taken to address the issue of climate change.While the large-scale challenges are critical, focusing on local challenges driven by climate change requires immediate action. One such local challenge is the impact of severe precipitation events. These events affect many sectors, from agriculture to urban infrastructure, but a particularly critical area is aviation safety. Unpredictable and intense precipitation, such as heavy rain or snow, can disrupt flight operations and pose serious risks. Radar technology has proven indispensable in detecting, tracking, and classifying severe precipitation events. It provides high-resolution data that is crucial for identifying and predicting severe weather. However, significant challenges remain, especially in accurately classifying precipitation types, detecting fast-evolving weather patterns, and optimizing radar systems for real-time response. This project addresses these challenges by improving radar-based detection and tracking methods using multiple beams simultaneously generated by the phased array radar PHARA.
Deadline : 15 March 2025
(30) PhD Degree – Fully Funded
PhD position summary/title: PhD Position Resilient Strategic Planning for Transport Network Development
The position is related to the Horizon Europe funded project called SCUDO that identifies and classifies scenarios of disruptive changes, assess their impact on different socio-economic groups, improves the monitoring of disruptions and the quantification of uncertainties, and develops methods for designing & managing transport systems. This will increase the resilience and safety of transport systems. Additionally, SCUDO aims to establish a Pan European Platform that integrates digital solutions and data in order to support a comprehensive evaluation of the impact of different types of disruptions to different geographical areas and user groups.
Amsterdam, the capital city of the Netherlands, is its most populated city, situated within the polycentric regions of North Holland and the Randstad. The Amsterdam Metropolitan Area has a population of about 2.5 million inhabitants and covers an area of 2,500.3 km², divided into more than 30 municipalities. The region boasts a robust rail system for inter-regional and international connections, alongside a dense network of roads, including a heavily used motorway system. Despite Amsterdam’s international fame as a cycling city, the region heavily relies on the motorized transport of goods and people (both private and public transport) to sustain its economic vitality and position as one of the most active and dynamic regions in the EU. Notably, the region is home to the 4th busiest airport in Europe, which virtually connects the area with the entire world. However, Amsterdam’s location below average sea level makes it particularly vulnerable to weather events that can disrupt this key EU region, moreover, growing energy consumption due to the increasing electrification of the country is leading to grid congestion and potential power outages. With the increasing likelihood of such events due to climate change, the risks for the region are significant. We aim to consider disruption scenarios related to (1) Extreme Weather Conditions/Climate Change, (2) Energy Disruptions, and (3) Supply-chain disruptions related to roads and waterways.
In this PhD, we focus on proactive and preventive mid to long-term measures and policies, particularly in designing transport networks and land use densification, to enhance the region’s resilience to extreme events. The methods developed in this project, utilizing data and forecasting, will enable the deployment of optimization techniques to guide investment decisions in both road and public transport networks (network arcs) and land use development (network nodes). These methods aim to maximize recovery and overall resilience, including safety, in the face of extreme climate events that need to be predicted through stress test models. Designing an extended transport network for increasing population needs to consider these contingencies to assure the safety of citizens and protect the infrastructure. From an operational perspective, during these events, proactive and reactive recourse actions are vital to restore essential passenger and freight transport to a level that allows the region to function, laying the groundwork for a quicker recovery.
Deadline : 10 March 2025
(31) PhD Degree – Fully Funded
PhD position summary/title: Postdoctoral Researcher on Microscale Modelling of Composites for Manufacturing Simulations
The aviation industry is confronted by the unique challenge, to achieve climate neutrality. This ambitious goal has profound implications requiring ultra efficient aircrafts, which require novel materials, production technologies and constructions. In this initiative Dutch companies and knowledge institutions work together to develop innovative solution for complex thermoplastic composite parts.
This postdoc position tackles the challenge of 3D microscale modelling of fiber-reinforced composites, with a focus on modelling the deformation of the constituents during the manufacturing stage. The thermplastic matrix region transitions from a viscous fluid to solid as temperature falls below the glass transition temperature. The fibers, embeded in the matrix region, may come into contact with each other during the process. Latest technologies on computational contact algorithms, fluid-structure interaction, particle methods, beam elements, etc., may be needed to effectively and efficiently simulate the deformation of such a material system during the manufacturing process. The objective is that such a numerical model would serve as a reliable virtual testbed to predict the influence of manufacturing conditions on the microscale properties of composites, e.g., the distributions of fiber density, waviness, and matrix defects.
Deadline : 31 March 2025
(32) PhD Degree – Fully Funded
PhD position summary/title: PhD Position AI-Driven Generative Engineering Design from Qualitative and Quantitative Requirements
We are seeking future trailblazers with motivation to transform the design process with Artificial Intelligence. At a high level, engineering design involves mapping a problem’s functional requirements to the physical parameters which define a solution. In the case of quantitative design objectives, processes like topology optimization can be utilized to converge on parameters which maximize performance. However, real-world requirements relating to societal, sustainable, and manufacturing needs are not necessarily easily quantified. Considering both qualitative and quantitative functional information together for design optimization is a complex challenge.
This position is an opportunity to connect recent advancements in AI such as language modeling and computer vision with fundamental Mechanical Engineering techniques such as topology optimization. This research involves the development of methods and tools to represent complex functional requirements and geometric form for generative design. The envisioned output of this project is a design representation model capable of encoding qualitative and quantitative design requirements together in a unified latent “semantic” space which can be used to generate geometrically optimized physical components. Success in this endeavor will mean a transformation of how multimodal data is utilized to maximize design performance and sustainability.
Deadline : 2 March 2025
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.
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