Composite structures in aerospace and wind energy are becoming larger, lighter, and more complex, while early-stage damage often remains invisible until critical failure occurs. In this PhD position, you will combine Quantum Photonic Vibrometry (QPV) with AI-driven vibration analysis to detect micro-scale damage at an early stage. You will work with leading academic and industry partners to develop safer and more sustainable engineering systems.
Job Description
As a PhD candidate at TU Delft, you will investigate how advanced vibration measurements and interpretable AI models can improve the early detection of structural damage in composite materials. Your research will focus on combining high-precision Quantum Photonic Vibrometry with machine learning techniques capable of identifying subtle changes in structural behaviour.
You will design and conduct vibration experiments using QPV sensing systems and analyse complex measurement data to identify signatures of micro-scale damage. In parallel, you will develop advanced and interpretable AI models for damage detection and condition monitoring, with a strong focus on robustness, explainability, and practical applicability.
Part of the project involves deploying lightweight AI models on reservoir computing devices and edge AI hardware, enabling efficient and scalable real-time monitoring solutions. You will collaborate closely with academic researchers and industrial partners, contributing to both fundamental research and application-driven innovation.
You will become part of a supportive and international research team within TU Delft, with access to state-of-the-art sensing facilities, advanced computational resources, and collaborative industrial environments. The position offers the opportunity to work at the intersection of quantum sensing, artificial intelligence, and structural integrity for aerospace and renewable energy applications.
Job Requirements
- A Master’s degree in engineering, physics, applied mathematics, or a related field.
- Affinity with vibration measurement and analysis, AI or machine learning, and/or signal processing.
- Experience with programming languages such as Python, MATLAB, or similar tools.
- An analytical and creative mindset with an interest in developing innovative methods.
- Strong problem-solving skills and the ability to work independently within a research project.
- Excellent English communication skills, both written and spoken.
- Interest in working in a multidisciplinary and international research environment.
- Motivation to contribute to research with societal and industrial impact in aerospace and renewable energy.
TU Delft
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 Aerospace Engineering
The Faculty of Aerospace Engineering at Delft University of Technology is a leading international community where innovation in aerospace meets global challenges. Our support and scientific staff, including PhD candidates, postdocs, and students, largely work together on three main themes: the energy transition, sustainable aerospace, and safety and security, with the aim of tackling climate change and contributing to the independence and security of Europe.
When you join us, you become part of a diverse, collaborative, and forward-thinking environment where your ideas and perspectives are valued. Our work extends beyond the lab—into field labs, innovation hubs, and partnerships with other faculties, research institutes, governments, and industry, both locally and globally.
We are committed to fostering an inclusive and welcoming workplace, assisted by an active Diversity & Inclusion team. This includes tangible support such as funding for extra personnel for family and caregiving responsibilities, mentoring programmes, and initiatives that promote cultural exchange and integration.
You don’t just join our faculty — you join a community where you can thrive, grow, and help shape the future of aerospace.
Click here to go to the website of the Faculty of Aerospace Engineering.
Conditions of employment
Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3059 - €3881 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.
As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.
Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.
Additional information
If you would like more information about this vacancy or the selection procedure, please contact Vahid Yaghoubi, via v.yaghoubi@tudelft.nl or .
Application procedure
Are you interested in this vacancy? Please apply no later than 28 Jun 2026 via the application button and upload the following documents:
- Detailed CV (up to two pages).
- Motivational letter (up to one page).
- BSc and MSc Transcripts.
- Master thesis and scientific papers that you have written in English.
You can address your application to Vahid Yaghoubi. Candidates will be evaluated on a rolling basis, so please apply as soon as possible.
Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.
Please note:
- You can apply online. We will not process applications sent by email and/or post.
- As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
- Applying for an exemption for specific research and educational areas is an obligatory part of the selection procedure for this vacancy. This exemption must be obtained from the Ministry of Education, Culture and Science (OCW) before an employment contract is agreed upon. Click here for more information.
- Please do not contact us for unsolicited services
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
The integration of high-precision sensing modalities into structural health monitoring represents a critical transition point for the aerospace and renewable energy value chains. As composite structures increase in geometric complexity and scale, classical vibration analysis faces deterministic limits in detecting sub-surface, micro-scale degradation before catastrophic failure. This role type exists to bridge the gap between fundamental quantum optics and industrial reliability engineering, utilizing Quantum Photonic Vibrometry to surpass the standard quantum limit of measurement. By establishing a high-fidelity data bridge between quantum-enhanced hardware and interpretable artificial intelligence, this function enables the transition from reactive maintenance to predictive, real-time structural intelligence. Market signals from the global sensing and integrated photonics sectors indicate that such cross-disciplinary expertise is essential for de-risking capital-intensive infrastructure in a transitioning energy economy.
The quantum sensing market is currently valued at several billion dollars and is projected to expand rapidly as industries seek to overcome the precision bottlenecks of classical instrumentation. Within the quantum value chain, the application of photonic sensors to structural integrity falls under the "Quantum Sensing and Metrology" layer, which is widely regarded as the most mature and commercially viable segment for near-term industrial impact. However, the ecosystem faces a significant Technology Readiness Level (TRL) mismatch between laboratory-grade quantum optical setups and the ruggedized requirements of field-deployed aerospace or wind energy systems.
Macro-level constraints in this domain are primarily characterized by the "translation gap"—the difficulty of integrating high-sensitivity quantum data into existing industrial decision-making frameworks. While quantum sensors can provide unprecedented resolution, the resulting data volumes and signal-to-noise complexities require a new tier of specialized workforce capable of developing hybrid classical-quantum analytical models. Current global workforce data suggests a critical scarcity of talent that possesses deep-tech fluency in both quantum physics and edge-deployed machine learning.
Furthermore, the industry is shifting toward a decentralized monitoring architecture where lightweight AI models are embedded directly onto hardware via reservoir computing or edge-processing units. This trend is driven by the need to reduce data latency and ensure the autonomous operation of critical infrastructure. As national quantum strategies increasingly prioritize the "quantum-classical interface," the ability to harmonize high-accuracy photonic measurements with robust, explainable AI becomes a strategic imperative for maintaining European engineering leadership in sustainable aerospace and energy sectors.
The capability architecture for this role centers on the convergence of quantum-enhanced metrology, non-destructive testing (NDT), and advanced computational intelligence. Mastery of the interface between quantum photonic sources and structural vibration modes is fundamental for ensuring data integrity at the primary sensing layer. This technical proficiency must be coupled with an understanding of hybrid analytical workflows, where high-dimensional data from photonic vibrometry is compressed and interpreted through interpretable AI architectures. Such capabilities are vital for structural throughput, as they allow for the identification of damage signatures that are statistically invisible to conventional piezoelectric or fiber-optic sensors.
Beyond hardware-software integration, the role requires expertise in the deployment of lightweight algorithms onto specialized hardware, such as neuromorphic or edge-AI devices. This interface ensures that the precision gains of quantum sensing are not lost to the latency of centralized cloud processing. By standardizing the translation of quantum optical signals into actionable condition-monitoring protocols, these experts facilitate the interoperability of deep-tech sensors with industrial-grade control systems. This strategic alignment is essential for the long-term stability and safety of next-generation composite structures in high-stress environments.
Accelerates the deterministic progression of structural health monitoring from classical limits to quantum-enhanced precision
Mitigates systemic risks in aerospace manufacturing by enabling the detection of micro-scale damage prior to structural propagation
Facilitates the transition toward autonomous maintenance cycles for offshore wind energy infrastructure through real-time sensing
Reduces lifecycle costs for capital-intensive composite structures via high-fidelity predictive analytics and condition monitoring
Strengthens the strategic autonomy of the European aerospace sector by securing early-mover expertise in quantum-enhanced NDT
Harmonizes abstract quantum optical research with the practical requirements of large-scale renewable energy systems
Optimizes the data-to-decision pipeline through the integration of explainable AI with high-precision photonic vibrometry
Supports the scaling of sustainable aviation by providing the metrological foundations for lighter and more complex airframes
Shortens the development cycle for advanced materials by establishing rigorous quantum-enhanced benchmarking and validation
Improves the reliability of multi-stakeholder engineering projects through the application of standardized quantum sensing protocols
Protects long-term investments in renewable energy by mitigating the impact of unplanned downtime and structural failure
Enables the strategic orchestration of deep-tech innovation across global networks of academic and industrial partners
Industry Tags: Quantum Sensing, Photonic Vibrometry, Structural Health Monitoring, Composite Materials, Aerospace Engineering, Explainable AI, Edge Computing, Quantum Metrology, Non-Destructive Testing
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