Scientific Assistant / Postdoc "Mapping Ukraine" on urban LiDAR scanning and machine learning in Zürich

To strengthen the team in the soon-to-be-launched project "Mapping Ukraine", the Chair of at the , headed by Prof. Catherine De Wolf, is looking to hire a scientific assistant.

"Mapping Ukraine" is a cooperation project with the chairs of Geoinformation Engineering (Prof. M. Raubal), Circular Engineering for Architecture (Prof. C. De Wolf) and Geosensors and Engineering Geodesy (Prof. A. Wieser) at the Department of Civil, Environmental and Geomatic Engineering. It aims to create an independent platform for open and intuitive access to verified, comprehensive, geo-referenced information on the impact of war, terrorism or natural disasters on buildings, civil infrastructure and agricultural land. Images, 3D models, already publicly available data and voluntarily provided geographic information (VGI) of selected test sites, including one in Ukraine, will be automatically collected, verified, tagged, integrated and made available as Spatio-temporal evidence for use by professionals such as researchers, engineers and journalists, as well as by the public.

• Collaboration in the research project "Mapping Ukraine" as a specialist in LiDAR scanning, computer vision and machine learning in an interdisciplinary and international team
• Development of tools for building damage and material volume estimation at the urban scale.
• Federation of city-scale LiDAR scans and image acquisition across multiple time frames
• Synthesis of existing street view datasets with live images from social media and other sources
• Detection and analysis of building and infrastructure damage in ongoing urban datasets using machine learning algorithms
• Extraction of volumetric information on building damage to inform reconstruction planning
• Support of the professorship in research and teaching in the fields of engineering geodesy/surveying /terrestrial laser scanning, if a degree of employment >50% is desired.

• You have a Master's degree or PhD in computer science, building technology or in a related discipline.
• Experience in application, research or development in the field of machine learning, LiDAR scanning, or GIS is recommended.
• You have good programming experience in Python and working with large data sets.
• You have experience with modern machine-learning frameworks.
• You are fluent in spoken and written English. Knowledge of German is an advantage. 
• Experience with geodetic practice, as well as implementation of web applications and machine learning, is an advantage.

We offer employment for an initial period of 1 year in an international, interdisciplinary, highly motivated and collaborative working environment. The level of employment can be adapted to your needs. Subsequently, an extension to a maximum of 6 years is possible, with or without taking up doctoral studies, depending on your qualifications.

You will have access to the excellent infrastructure of ETH Zurich, the many contacts of the chair to other research institutions, the industry and authorities as well as to the extensive and modern equipment of the IGP. You will appreciate the opportunity to gain experience through exchanges with the De Wolf, Raubal and Wieser chairs, the opportunity to work on other projects on a selective basis, the high quality of life in the Zurich area, as well as ETH Zurich's offer of continuing education and development opportunities.

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our to find out how we ensure a fair and open environment that allows everyone to grow and flourish.