PhD in Multi-modal AI for UAV-based Structural Defect Analysis

Introduction
Are you passionate about AI, multi-modal sensing, and resilient infrastructure? Would you like to integrate advanced AI techniques with heterogeneous UAV-based sensor data for the inspection and maintenance of critical transportation infrastructure, addressing real-world challenges faced by industry, governments, and society within the international STRUCTURE project?

Job Description
The PhD candidate will work within the international research project STRUCTURE in cooperation with industrial partners from the Netherlands, the United Kingdom, Belgium, Turkey, and Portugal. The project aims to automate and enhance inspection of transportation infrastructure through multi-modal sensing, autonomous UAV platforms, and advanced AI-based analysis. A central focus is the detection of defects in bridges and viaducts using X-ray, LiDAR, visual and acoustic data captured from UAVs.

The research will address the design of AI models capable of combining heterogeneous sensor modalities, including RGB, thermal, LiDAR, acoustic arrays, GPR, and X-ray backscatter, to create a unified and reliable representation of structural integrity. The work expands on TU/e’s contributions by developing algorithmic components for detection and classification of defects and anomalies across both surface and subsurface layers. This includes constructing robust feature extraction pipelines, attention-based fusion architectures, and deep learning models that accurately characterize cracks, voids, delamination, corrosion, and internal structural discontinuities. The PhD candidate will investigate Vision Language Models (VLMs), Multi-modal AI solutions, and 3D scene reasoning approaches, to achieve spatial understanding and cross-modal representation learning from heterogeneous sensor data, with the research not limited to these methods. This research will support semantic interpretation, defect localization, temporal reasoning, and predictive maintenance in complex inspection environments.

A second contribution involves predictive maintenance algorithms that integrate static data sources (such as geological maps, material properties, and usage profiles) with dynamic sensor measurements (including pressure, vibration, visual, acoustic, and X-ray signals). The PhD candidate will investigate temporal modelling, multimodal analysis, and risk progression modelling to forecast deterioration patterns and estimate the remaining useful lifetime of infrastructure components. The research also encompasses model compression and optimization for edge deployment on UAV-mounted processors to support real-time inference. The candidate will collaborate with industrial partners for real-world data acquisition and large-scale validation on operational bridges and viaducts.

Research group and company
The PhD student will be working in the AIMS laboratory of the Signal Processing Systems (SPS) group within the Department of Electrical Engineering at TU/e. The AIMS lab researches and develops AI models for systems equipped with sensors of multiple different modalities. We foster expertise in AI analysis of RGB, thermal, depth, LiDAR, acoustic, sonar and radar sensor data, with established research lines in 3D reconstruction, and Edge AI for resource-constrained deployments.

Job Requirements

• A master’s degree in Electrical Engineering, Computer Science, Artificial Intelligence or in a strongly related discipline.
• Experience with deep learning framework PyTorch or similar.
• Strong background in machine learning, image or signal processing.
• Knowledge of SotA models for multi-modality and scene understanding.
• Experience with multi-modal sensor data, such as X-ray, LiDAR, visual, acoustic, thermal, or GPR.
• Ability to work in an interdisciplinary team and interested in collaborating with industrial partners.
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level).

Conditions of Employment
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 3,059 - max. € 3,881).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• Unlimited access to the modern on‑campus TU/e Student Sports Center at an exceptionally affordable rate, for you and, if applicable, your partner.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

About us
We are a leading international university where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact — today and in the future. TU/e is home to over 13,000 students and more than 7,000 staff, forming a diverse and vibrant academic community.

Our university is located in Brainport Eindhoven — a world‑leading tech region with more than 7,000 high‑tech companies and strong R&D activity. Known for breakthroughs in AI, photonics, semiconductors and advanced manufacturing, Brainport is a place where technology serves people and society. Learn more about the Brainport region here.

The mission of the Department of Electrical Engineering is to acquire, share and transfer knowledge and understanding in the whole field of Electrical Engineering through education, research and valorization. We work towards a ‘Smart Sustainable Society’, a ‘Connected World’, and a healthy humanity (‘Care & Cure’). Activities share an application-oriented character, a high degree of complexity and a large synergy between multiple facets of the field.

Research is carried out into the applications of electromagnetic phenomena in all forms of energy conversion, telecommunication and electrical signal processing. Existing and new electrical components and systems are analyzed, designed and built. The Electrical Engineering department takes its inspiration from contacts with high-tech industry in the direct surrounding region and beyond.

The department is innovative and has international ambitions and partnerships. The result is a challenging and inspiring setting in which socially relevant issues are addressed.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Dr.ir. Egor Bondarev, e.bondarev@tue.nl, Head of AIMS lab, and dr. Erkut Akdag e.akdag@tue.nl, PostDoc researcher in AIMS lab.

Visit our website for more information about the application process or the conditions of employment. You can also contact Floor de Groot, HR advisor, f.r.d.groot@tue.nl or +31 40 247 3040.

Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application
We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.

Ensure that you submit all the requested application documents. We give priority to complete applications.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check, please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.

PhD in Multi-modal AI for UAV-based Structural Defect Analysis

The PhD candidate will work within the international research project STRUCTURE in cooperation with industrial partners from the Netherlands, the United Kingdom, Belgium, Turkey, and Portugal. The project aims to automate and enhance inspection of transportation infrastructure through multi-modal sensing, autonomous UAV platforms, and advanced AI-based analysis. A central focus is the detection of defects in bridges and viaducts using X-ray, LiDAR, visual and acoustic data captured from UAVs.

The research will address the design of AI models capable of combining heterogeneous sensor modalities, including RGB, thermal, LiDAR, acoustic arrays, GPR, and X-ray backscatter, to create a unified and reliable representation of structural integrity. The work expands on TU/e’s contributions by developing algorithmic components for detection and classification of defects and anomalies across both surface and subsurface layers. This includes constructing robust feature extraction pipelines, attention-based fusion architectures, and deep learning models that accurately characterize cracks, voids, delamination, corrosion, and internal structural discontinuities. The PhD candidate will investigate Vision Language Models (VLMs), Multi-modal AI solutions, and 3D scene reasoning approaches, to achieve spatial understanding and cross-modal representation learning from heterogeneous sensor data, with the research not limited to these methods. This research will support semantic interpretation, defect localization, temporal reasoning, and predictive maintenance in complex inspection environments.

A second contribution involves predictive maintenance algorithms that integrate static data sources (such as geological maps, material properties, and usage profiles) with dynamic sensor measurements (including pressure, vibration, visual, acoustic, and X-ray signals). The PhD candidate will investigate temporal modelling, multimodal analysis, and risk progression modelling to forecast deterioration patterns and estimate the remaining useful lifetime of infrastructure components. The research also encompasses model compression and optimization for edge deployment on UAV-mounted processors to support real-time inference. The candidate will collaborate with industrial partners for real-world data acquisition and large-scale validation on operational bridges and viaducts.

Research group and company
The PhD student will be working in the AIMS laboratory of the Signal Processing Systems (SPS) group within the Department of Electrical Engineering at TU/e. The AIMS lab researches and develops AI models for systems equipped with sensors of multiple different modalities. We foster expertise in AI analysis of RGB, thermal, depth, LiDAR, acoustic, sonar and radar sensor data, with established research lines in 3D reconstruction, and Edge AI for resource-constrained deployments.

PhD on Multi‑Domain System Topology Design Automation

Introduction
Do you like applying mathematical theories in practice to solve real-world challenges? Do you like working with top-notch, internationally recognized industrial partners? Would you like to push the boundaries of system-level modelling, analysis, design, exploration and synthesis beyond the current state-of-the-art? Or are you curious to learn more about the application of AI for system design? We are offering a PhD position to join our research team for an interdepartmental project focused on solving cutting-edge design automation questions that will drive innovation in the Brainport region and beyond.

Job Description
The semiconductor industry is essential to global economic growth and technological progress, enabling innovations ranging from advanced energy solutions to next‑generation healthcare. While parts of high‑tech system design—such as the design of lithography machines—can already be automated, current design‑automation tools remain limited to specific domains or subsystems. Given the growing complexity of these systems, holistic system‑level design automation is the logical and necessary next step. Achieving this requires moving beyond domain‑specific solutions by integrating mechanical, electrical, software, data‑science, and AI expertise.

We are seeking a highly motivated candidate for the PhD position described here, who will contribute to this challenge by advancing system‑level co‑design of architecture, functionality, and performance. You will join a team consisting of five other PhD researchers and colleagues from two additional departments (Electrical Engineering, and Mathematics & Computer Science). The team develops in addition system models to monitor and understand operational behavior and to act upon system irregularities.

This PhD research focuses on achieving automated computational design synthesis of system topologies—that is, how components and subsystems can be interconnected to realize a functional system. The goal is to generate new and innovative system topologies that can be automatically analyzed and evaluated based on construction properties and performance indicators. This requires insights into how to fully automate discrete topology‑design synthesis across system levels, how to learn component descriptions, and how these components can be interconnected.

We are looking for a candidate with strong programming skills; prior experience in applying and understanding generative AI methods and tools; and a solid background in system‑design methodologies. A keen interest in complex dynamical systems, functional and performance engineering, multi-domain methods, learning techniques, and optimization is essential.

Job Requirements

• A master’s degree (or an equivalent university degree) in systems and control, mechanical engineering, electrical engineering, mathematics and/or computer science.
• Strong analytical and problem-solving skills, with a passion for tackling complex, multi-disciplinary challenges.
• Eager to work within an interdisciplinary team of industry and academic researchers.
• Excellent communication and collaboration skills to work effectively within a large project team.
• Proven programming skills in Matlab and/or Python
• Motivated to develop your teaching skills and coach students
• Fluent in spoken and written English (C1 level)

Conditions of Employment
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 3,059 - max. € 3,881).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• Unlimited access to the modern on‑campus TU/e Student Sports Center at an exceptionally affordable rate, for you and, if applicable, your partner.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

About us
We are a leading international university where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact — today and in the future. TU/e is home to over 13,000 students and more than 7,000 staff, forming a diverse and vibrant academic community.

Our university is located in Brainport Eindhoven — a world‑leading tech region with more than 7,000 high‑tech companies and strong R&D activity. Known for breakthroughs in AI, photonics, semiconductors and advanced manufacturing, Brainport is a place where technology serves people and society. Learn more about the Brainport region here.

The Department of Mechanical Engineering department conducts world-class research aligned with the technological interests of the high-tech industry in the Netherlands, with a focus on the Brainport region. Our goal is to produce engineers who are both scientifically educated and application-driven by providing a balanced education and research program that combines fundamental and application aspects. We equip our graduates with practical and theoretical expertise, preparing them optimally for future challenges.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Theo Hofman, Full professor, t.hofman@tue.nl or +31 40 247 2827.

Visit our website for more information about the application process or the conditions of employment. You can also contact HRServices.me@tue.nl.

Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application
We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.

Ensure that you submit all the requested application documents. We give priority to complete applications.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check, please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.

PhD on Multi‑Domain System Topology Design Automation

The semiconductor industry is essential to global economic growth and technological progress, enabling innovations ranging from advanced energy solutions to next‑generation healthcare. While parts of high‑tech system design—such as the design of lithography machines—can already be automated, current design‑automation tools remain limited to specific domains or subsystems. Given the growing complexity of these systems, holistic system‑level design automation is the logical and necessary next step. Achieving this requires moving beyond domain‑specific solutions by integrating mechanical, electrical, software, data‑science, and AI expertise.

We are seeking a highly motivated candidate for the PhD position described here, who will contribute to this challenge by advancing system‑level co‑design of architecture, functionality, and performance. You will join a team consisting of five other PhD researchers and colleagues from two additional departments (Electrical Engineering, and Mathematics & Computer Science). The team develops in addition system models to monitor and understand operational behavior and to act upon system irregularities.

This PhD research focuses on achieving automated computational design synthesis of system topologies—that is, how components and subsystems can be interconnected to realize a functional system. The goal is to generate new and innovative system topologies that can be automatically analyzed and evaluated based on construction properties and performance indicators. This requires insights into how to fully automate discrete topology‑design synthesis across system levels, how to learn component descriptions, and how these components can be interconnected.

We are looking for a candidate with strong programming skills; prior experience in applying and understanding generative AI methods and tools; and a solid background in system‑design methodologies. A keen interest in complex dynamical systems, functional and performance engineering, multi-domain methods, learning techniques, and optimization is essential.

PhD in Photonic Integrated Circuit-Assisted Nanowire-Based Neuromorphic Computing – PHINDER project

Introduction
The Photonic Neural Network Lab of the Electro-Optics Communication (ECO) group at Eindhoven University of Technology (TU/e) is recruiting a PhD candidate to research novel integrated-photonics-assisted nanowire neuromorphic computing.

Job Description
The electro-optical communications (ECO) group in the Faculty of Electrical Engineering at TU/e is a globally recognised, leading scientific and applied research group focused on exploiting light for communication and quantum systems. We apply our knowledge in collaboration with other scientists at TU/e and more recently within the newly formed Casimir Institute to develop the required solution for many of the relevant challenges in communication and sensing systems. The group expertise spans from the fundamentals and physics of photonics, optics, the design and fabrication of photonic integrated circuits (PICs) for computing and communications, systems engineering to exploiting optical linear/non-linear signal processing to unlock fiber capacity and relevant higher layer protocols required to operate modern optical communication and quantum networks.

Based in the purposely built FLUX building at the TU/e Campus, the ECO group has access to 300m2 of labs for conducting experimental research and is supported by a state-of-the-art 800m2 cleanroom. With greater than 100 group members including 13 tenured scientists, 79 PhD candidates, 16 postdocs and senior researchers, the ECO group is a vibrant and exciting research group perfectly suited for talented and ambitious scientists. The group is active in spin outs and starts-ups (e.g. CubiQ, Micro-align, PhotonX Networks and LuXisens Technology) and carries out bilateral industrial research with major stakeholders in the communications industry.

Job Requirements
As demand for edge computing grows, there is an increasing need for systems capable of processing data locally with minimal latency and low energy consumption. Traditional computing architectures based on CMOS technology and the von Neumann model struggle to meet these requirements, as the separation of memory and processing units leads to data-transfer bottlenecks and increased power consumption.

PHINDER, short for Picosecond-scale Photonic Heterogeneous Integrated Neuromorphic Detector, is a European research initiative funded by the EIC Pathfinder 2025 program, bringing together leading academic institutions and innovative companies to address these challenges. The project aims to develop neuromorphic photonic sensor systems capable of analysing light signals from complex processes at the picosecond scale while operating with extremely low energy consumption. The platform combines nanostructured III–V semiconductor nanowires, programmable photonic waveguides, and neuromorphic sensor arrays into a unified hardware system that processes time-varying optical signals directly on-chip.

Coordinated by Luleå University of Technology, the consortium includes Lund University, NanoLund, Eindhoven University of Technology, Universidad de Oviedo, Universidad de Cantabria, Istituto Nazionale di Fisica Nucleare, and Hewlett Packard Enterprise.

The project develops nanowire-based optoelectronic devices integrated with InP photonic circuits to realize photonic spiking neural networks. By combining modelling, fabrication, and hybrid nanowire–waveguide integration, the project aims to enable ultrafast and energy-efficient optical signal processing and demonstrate its potential for advanced sensing and data-processing applications. The modelling work focuses on the design and simulation of the nanowire–photonic interface and the overall photonic neural network architecture. Eindhoven University of Technology will study optical coupling between nanowires and InP waveguides using different approaches to achieve efficient low-loss light transfer. The work also investigates nanophotonic structures to address optical mode mismatches and uses device-level simulations to support system-level network design. The fabrication work aims to develop a planar InP photonic platform capable of integrating nanowire devices with photonic integrated circuits. This includes the development of waveguide-based photonic circuits and coupling structures enabling hybrid nanowire integration. Additional activities involve device integration, electrical contacting, and chip packaging to enable experimental testing. The final phase focuses on the experimental demonstration of photonic spiking neural network architectures. This includes characterization of nanowire optoelectronic devices, evaluation of coupling structures, and testing of reconfigurable photonic circuits implementing neural network connectivity. Experimental validation will assess the performance of the platform for representative signal-processing tasks.

The ideal candidate must have:

• A master’s degree (or an equivalent university degree) in photonics, electro, applied physics or similar.
• A strong background in integrated photonics, preferably on III–V or InP platforms, with hands-on experience in waveguide and coupler design using electromagnetic simulation tools
• Experience with reconfigurable photonic circuits, such as Mach–Zehnder interferometer meshes, and an interest in photonic or neuromorphic computing are highly desirable.
• The candidate should be familiar with cleanroom fabrication processes for photonic integrated circuits and with experimental characterization of photonic devices, including ultrafast or time-resolved optical measurements.
• A systems-oriented mindset is essential, with the ability to translate device-level parameters into circuit- and system-level performance metrics.
• Strong interdisciplinary collaboration skills are required, enabling effective interaction with experts in nanowire devices, neuromorphic algorithms, and system simulation.
• Excellent scientific communication skills and the ability to contribute to an international research consortium are also expected.
• He/she should be fluent in spoken and written English (C1 level).

Conditions of Employment
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 3,059 - max. € 3,881).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• Unlimited access to the modern on‑campus TU/e Student Sports Center at an exceptionally affordable rate, for you and, if applicable, your partner.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

About us
We are a leading international university where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact — today and in the future. TU/e is home to over 13,000 students and more than 7,000 staff, forming a diverse and vibrant academic community.

Our university is located in Brainport Eindhoven — a world‑leading tech region with more than 7,000 high‑tech companies and strong R&D activity. Known for breakthroughs in AI, photonics, semiconductors and advanced manufacturing, Brainport is a place where technology serves people and society. Learn more about the Brainport region here.

The mission of the Department of Electrical Engineering is to acquire, share and transfer knowledge and understanding in the whole field of Electrical Engineering through education, research and valorization. We work towards a ‘Smart Sustainable Society’, a ‘Connected World’, and a healthy humanity (‘Care & Cure’). Activities share an application-oriented character, a high degree of complexity and a large synergy between multiple facets of the field.

Research is carried out into the applications of electromagnetic phenomena in all forms of energy conversion, telecommunication and electrical signal processing. Existing and new electrical components and systems are analyzed, designed and built. The Electrical Engineering department takes its inspiration from contacts with high-tech industry in the direct surrounding region and beyond.

The department is innovative and has international ambitions and partnerships. The result is a challenging and inspiring setting in which socially relevant issues are addressed.

Information
Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Patty Stabile, Associate professor, r.stabile@tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact HRServices.ee@tue.nl.

Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application
We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.

Ensure that you submit all the requested application documents. We give priority to complete applications.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Please note

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check, please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.