PhD: 3D Heritage Digital Twins & Multimodal Sensing

Immigration Policy Lab; Zürich; On-site; CHF 60,000 - 76,000; Full time

Benefits offered by this job

Fully funded four-year doctoral posisi

State-of-the-art sensing equipment

Collaborative international team

Job summary

ETH Zurich's Chair of Geosensors and Engineering Geodesy invites applications for a Doctoral candidate to develop 3D mapping, scene reconstruction and multi-modal sensing for information-rich digital twins of stone-built heritage.

Join the HC3 project and collaborate across departments to advance LiDAR and imaging-based sensing, data fusion and HBIM generation, with opportunities to publish and teach; funding is provided for four years.

Qualifications

• MSc degree in geomatics, remote sensing, computer vision, robotics or related field.
• Strong background in 2D/3D perception (point cloud and image processing) and machine/deep learning; good programming skills in Python or C++.
• Willingness to perform fieldwork on monuments; English proficiency; French or German is a plus.

Responsibilities

• Plan and carry out multi-sensor mapping campaigns of monuments (LiDAR and imaging) using ground-based and UAV platforms.
• Calibrate, register and fuse point clouds and imagery into unified 3D representations (point clouds, meshes, neural radiance fields, 3D Gaussian splatting).
• Develop deep learning methods to segment scenes for automated digital twin (HBIM) generation.
• Infer material properties from multi-modal data and time series; collaborate on integrating data into digital twins and XR; publish results and contribute to teaching.

Skills

3D perception

Python

C++

Education

MSc in geomatics/remote sensing/computer vision

Tools

LiDAR

Imaging systems

Job description

ETH Zurich's Chair of Geosensors and Engineering Geodesy invites applications for a Doctoral candidate to develop 3D mapping, scene reconstruction and multi-modal sensing for information-rich digital twins of stone-built heritage.

Join the HC3 project and collaborate across departments to advance LiDAR and imaging-based sensing, data fusion and HBIM generation, with opportunities to publish and teach; funding is provided for four years.