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

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

Organisation/Company ETH Zürich Research Field Computer science » Other Engineering » Other Environmental science » Earth science Researcher Profile First Stage Researcher (R1) Application Deadline 31 Jan 2027 - 22:59 (UTC) Country Switzerland Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

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

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).

• 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 We value diversity and sustainabilityIn line with our values , ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate-neutral future .Curious? So are we.

Further information about the Department (D-BAUG), the Institute (IGP), and the Research group (GSEG)can be found on our websites: DBAUG , IGP , GSEG . Questions regarding the position should be directed to Tomislav Medic , [e-mail] (no applications).

About ETH ZürichETH Zurich is one of the world’s leading universities specialising in
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