Natural and human-made disasters can cause widespread devastation in urban areas, impacting thousands of lives and resulting in extensive property damage. In densely populated areas, rapid and accurate assessment of structural stability, i.e. the stability of man-made structures like bridges and buildings, is important for effective emergency response. Providing reliable recommendations is critical to ensure swift, informed decisions to minimize harm and expedite recovery. These should help first responders to make the decisions on where and when to prioritize their activities. Careful monitoring and dedicated analysis offer the proper background to guide such response strategies, ultimately saving lives and reducing overall damage.

Multitemporal Synthetic Aperture Radar (SAR) images contain important information well-established for structural stability or health monitoring. Such technologies, like SAR interferometry (InSAR) and SAR tomography (TomoSAR), can provide information on urban structure elevation and subtle deformations or stability issues. This information, however, is often sparse in time or space as it relies on identifying coherent scatterers. The use of AI and quantum computing to integrate SAR-derived products with real-time UAV optical data can offer reliable recommendations to prioritize areas where first responders are needed.

The HURRICANE project, funded by Horizon Europe, focuses on real-time intelligence for crisis and natural emergencies. It brings together scientists and partners from a multidisciplinary consortium of 15 partners and it addresses the limitations hindering the adoption of innovations in the field of real-time awareness. One of the project's primary objectives is to combine space-based SAR data with real-time UAV optical data to provide reliable near-real-time recommendations for first responders. Addressing this research question will be the main objective of this position.

You are encouraged to conduct interdisciplinary and innovative research in the field of SAR remote sensing and machine learning. Additionally, you will attend project meetings, liaise with project partners and the public, and contribute to the education programs at ITC.

The project is set to commence on January 1, 2025, and will run for four years. You will be expected to develop Python-based automation code to generate near-real-time recommendation maps by the end of December 2027.

• An MSc degree in radar remote sensing or related field
• A strong passion for research
• The ability to work on real-world problems in an interdisciplinary and internationally oriented environment
• Good communication skills and an excellent command of English. Fluency in Dutch or willingness to learn Dutch is a plus
• Knowledge of programming, SAR data, machine learning, advance computing models

Interested and motivated candidates are encouraged to apply, even when they still need to possess all desired skills. You can develop relevant skills on the job through dedicated learning and doctoral training.

• An inspiring multidisciplinary, international and academic environment. The university offers a dynamic ecosystem with enthusiastic colleagues in which internationalization is an important part of the strategic agenda
• Full-time position for 4 years
• A professional and personal development programme within Twente Graduate School
• Gross monthly salary of € 2,872.- in the first year that increases to € 3,670.- in the fourth year
• A holiday allowance of 8% of the gross annual salary and a year-end bonus of 8.3%
• Excellent support for research and facilities for professional and personal development
• A solid pension scheme
• A total of 41 holiday days per year in case of full-time employment
• Excellent working conditions, an exciting scientific environment, and a green and lively campus.

The department of Earth Observation Science deals with earth observation technology for problem-solving. Problem-solving means primarily the identification of solutions for large-volume producers of geo-information and the identification of solutions for application domains. The department is involved in teaching Masters of Geo-Information and Masters of Robotics. The department is also part of the Robotics Center of the University of Twente.