Fully Funded PhD: 3D Heritage Digital Twins & Sensing

ETH Zürich; Zürich; On-site; CHF 60,000 - 80,000; Full time

Job summary

ETH Zürich's Chair of Geosensors and Engineering Geodesy seeks a Doctoral candidate to advance 3D mapping, scene reconstruction and multi-modal sensing for information-rich digital twins of heritage buildings.

The HC3 project aims to develop interoperable 3D models of stone monuments using LiDAR, imaging, and XR, with fieldwork on monuments and collaboration with material scientists and conservation practitioners.

Qualifications

• MSc degree (completed or about to be completed) in geomatics, remote sensing, computer vision, robotics, computer science or a related field
• Solid background in 2D/3D perception (point cloud and image processing, photogrammetry, 3D reconstruction) and in parameter estimation, incl. machine and deep learning; good programming skills (Python or C++)
• Hands-on experience with laser scanning (LiDAR) or imaging systems is an advantage, and willingness to do fieldwork on monuments is a must
• Interest in interdisciplinary work with material scientists and conservation practitioners; excellent English; French or German is an advantage

Responsibilities

• Reality capture at scale: Plan and carry out multi-sensor mapping campaigns of monuments (including LiDAR and imaging technologies using ground-based and UAV platforms)
• Multi-modal data fusion and 3D scene reconstruction: Calibrate, register and fuse point clouds and imagery into unified, data-rich 3D representations (point clouds, meshes, neural radiance fields, 3D Gaussian splatting)
• 3D scene parsing: Develop deep learning enabled methods that segment the scene into individual building elements (stone blocks) for automated digital twin (HBIM) generation
• Inference of material properties: Develop machine learning methods that infer building material properties (stone deterioration type and severity) per element from multi-modal data and time series
• Collaborate on integrating this data into digital twins and extended reality, validate your methods against conservation expert assessments and physical chemistry laboratory experiments; publish in leading journals and conferences; contribute to teaching (upon agreement)

Skills

2D/3D perception

Point cloud processing

Image processing

Photogrammetry

3D reconstruction

Python

C++

Fieldwork readiness

Education

MSc degree

Geomatics / Remote sensing

Related field

Tools

LiDAR

Imaging systems

HBIM software

Job description

ETH Zürich's Chair of Geosensors and Engineering Geodesy seeks a Doctoral candidate to advance 3D mapping, scene reconstruction and multi-modal sensing for information-rich digital twins of heritage buildings.

The HC3 project aims to develop interoperable 3D models of stone monuments using LiDAR, imaging, and XR, with fieldwork on monuments and collaboration with material scientists and conservation practitioners.