Fully funded PhD Humanities & Arts Switzerland

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

ETH Zurich, Switzerland

Institution: ETH Zurich
Country: Switzerland
Position type: PhD
Subject area: Humanities & Arts
Funding: Fully funded position

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About this position

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

100%, Zurich, fixed-term

Drucken

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 lead by Prof. Robert Flatt at Chair of Physical Chemistry of Building Materials and by dr. Tomislav Medic at Chair 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

Workplace

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.

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We value diversity and sustainability

In 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.

We look forward to receiving your online application with the following documents:

CV, including a list of publications (if applicable)
Cover Letter, including the following two elements: A brief description (max. 1/2 A4 page + 1 figure) of a result from your previous work that you are proud of and presents relevant skills for this project and a brief description (max. 1/2 A4 page) of your vision of your Doctoral research project
Names and contact information of two references
Copy of your MSc degree/diploma

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, tmedic@ethz.ch (no applications).

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.

About ETH Zürich

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

Curious? So are we.

We look forward to receiving your online application with the following documents:

CV, including a list of publications (if applicable)
Cover Letter, including the following two elements: A brief description (max. 1/2 A4 page + 1 figure) of a result from your previous work that you are proud of and presents relevant skills for this project and a brief description (max. 1/2 A4 page) of your vision of your Doctoral research project
Names and contact information of two references
Copy of your MSc degree/diploma

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.

About ETH Zürich

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