Fully Funded PhD in 3D Heritage Digital Twins & Sensing

Academic Positions; Schweiz; On-site; CHF 60,000 - 70,000; Full time

Job summary

ETH Zürich is offering a fully funded four-year Doctoral Position on 3D scene reconstruction and multi-modal sensing for digital twins of stone-built heritage. The role focuses on planning multi-sensor campaigns, calibrating and fusing LiDAR and imagery, and developing deep learning methods for HBIM-enabled heritage models.

You will collaborate across departments and contribute to dissemination of results. The successful candidate will work with ETH Zurich’s renowned teams, engage in

Qualifications

• MSc degree (completed or about to be completed) in geomatics, remote sensing, computer vision, robotics, computer science or a related field.
• Strong background in 2D/3D perception and in parameter estimation incl. machine/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 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

Photogrammetry

3D reconstruction

Python/C++

Education

MSc in geomatics/remote sensing/ computer vision

Tools

LiDAR hardware

Ground-based imaging

Job description

ETH Zürich is offering a fully funded four-year Doctoral Position on 3D scene reconstruction and multi-modal sensing for digital twins of stone-built heritage. The role focuses on planning multi-sensor campaigns, calibrating and fusing LiDAR and imagery, and developing deep learning methods for HBIM-enabled heritage models.

You will collaborate across departments and contribute to dissemination of results. The successful candidate will work with ETH Zurich’s renowned teams, engage in