Doctoral Position: 3D scene reconstruction and multi-modal sensing for digital twins of stone-built heritage

ETH Zürich; 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

The Chair of Geosensors and Engineering Geodesy at ETH Zurich is looking for a Doctoral candidate to work on 3D mapping, scene reconstruction and multi-modal sensing for information-rich digital twins of heritage buildings.The position is part of the collaborative project “HC3 – Heritage Conservation Collaboration Copilots”.HC3 aims to establish information-rich 3D digital twins of stone-built monuments that are interoperable through eXtended Reality (XR), together with the sensing and monitoring methods that provide the data they are built on. These will help us model and understand how stone-built heritage deteriorates, and predict how this deterioration will evolve under climate change. Within the project, you would collaborate with two other Doctoral students employed by the Chair of Physical Chemistry of Building Materials at ETH Zurich and a postdoctoral researcher working on the interface of both Chairs. The HC3 project is leadbyProf. Robert Flatt at Chair of Physical Chemistry of Building Materialsand by dr. Tomislav Medic atChair of Geosensors and Engineering Geodesy (Tomislav would be your direct supervisor).

Job description

• 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)

Profile

• 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
• Further requirements: Interest in interdisciplinary work with material scientists and conservation practitioners; excellent English; French or German is an advantage

We offer

A fully funded four-year doctoral position in an international, dynamic team of highly motivated and supportive colleagues, state-of-the-art sensing equipment, and work on a project with a potential to evolve beyond the initial scope. ETH Zurich offers excellent infrastructure, continuing education and a salary according to ETH regulations, in a city with outstanding quality of life.

Working, teaching and research at ETH Zurich

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About ETH Zürich

ETH Zurich is one of the world’s leading universities specialising inscience and technology. We are renowned for our excellent education,cutting-edge fundamental research and direct transfer of new knowledgeinto society. Over 30,000 people from more than 120 countries find ouruniversity to be a place that promotes independent thinking and anenvironment that inspires excellence. Located in the heart of Europe,yet forging connections all over the world, we work together todevelop solutions for the global challenges of today and tomorrow.