PhD: 3D Heritage Digital Twins & Multi-Modal Sensing

ETH Zurich; Zürich; On-site; CHF 52,000 - 68,000; Full time

Benefits offered by this job

Fully funded PhD

Sensing equipment

Job summary

ETH Zurich invites applications for a Doctoral candidate to advance 3D mapping, scene reconstruction, and multi-modal sensing for heritage buildings. The project HC3 focuses on information-rich 3D digital twins interoperable via XR, in collaboration with two other ETH Chairs.

The role includes field campaigns, data fusion, and HBIM generation, with emphasis on machine learning, 3D reconstruction, and interdisciplinary collaboration. A funded four-year PhD position awaits the successful candidate.

Qualifications

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

Responsibilities

• Reality capture at scale with multi-sensor campaigns (LiDAR and imaging) on monuments.
• Develop multi-modal data fusion and 3D scene reconstruction methods (point clouds, meshes, neural radiance fields, 3D Gaussian splatting).
• Create 3D scene parsing methods to segment building elements for HBIM generation.
• Infer material properties from multi-modal data and time series; contribute to digital twins and XR integration; publish findings.

Skills

2D/3D perception

Point cloud processing

Python

C++

Education

MSc degree

Tools

LiDAR

Imaging systems

Job description

ETH Zurich invites applications for a Doctoral candidate to advance 3D mapping, scene reconstruction, and multi-modal sensing for heritage buildings. The project HC3 focuses on information-rich 3D digital twins interoperable via XR, in collaboration with two other ETH Chairs.

The role includes field campaigns, data fusion, and HBIM generation, with emphasis on machine learning, 3D reconstruction, and interdisciplinary collaboration. A funded four-year PhD position awaits the successful candidate.