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 integrateadvanced AI techniques with heterogeneous UAV-based sensor data for the inspection and maintenance ofcritical transportation infrastructure addressing real-world challenges faced by industry governments andsociety 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/es 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 masters 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 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. 3059 - max. 3881).
• 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 childrens day care and sports facilities.
• Unlimited access to the modern oncampus 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 13000 students and more than 7000 staff forming a diverse and vibrant academic community.

Our university is located in Brainport Eindhoven a worldleading tech region with more than 7000 hightech 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 . Egor Bondarev Head of AIMS lab and dr. Erkut Akdag PostDoc researcher in AIMS lab.

Visit our website for more information about the application process or the conditions of employment. You can also contactFloor de Groot HR advisoror.

Curious to hear more about what its 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.