Postdoc Researcher Digital Underground - Automatic Asset Detection for 3D Mapping of Underground Utilities
We are looking for talented and motivated individuals to join our team in Singapore and research and develop accurate, rapid, and cost-effective 3D mapping solutions for underground utilities. You will have the chance to build and develop a complete prototype, test and improve it through real-world sites and use cases, and work closely together with excellent academic peers from Switzerland and Singapore and local government and industry stakeholders.
To create new space for its growing needs, Singapore is going underground. Reliable and accurate information of underground utilities is a key enabler of good and efficient decisions made by planners, land administrators, developers and engineers. Conversely, a lack of reliable information can lead to a less than optimal use of underground space, lengthy and costly planning, design and development processes, and risks to critical infrastructure resilience workers' safety. However, due to a lack of resources, time, and capabilities, reliable information of underground utilities is often not captured, consolidated or shared in a sufficient manner.
In this project, we aim to make a significant contribution to solving this pressing problem both in Singapore and globally. We will research, develop, demonstrate, and evaluate an integrated, rapid, and cost-effective workflow in a realistic setting. The workflow will comprise 1) capturing newly built services and assets on-site, 2) providing a reliable 3D representation and associated documentation of these services and assets, and 3) their visualisation after covering up.
Starting in June 2020, you will work on the design and implementation of a system to detect underground utility assets in raw point cloud data.
You will join us in Singapore as part of an exciting new collaboration between ETH Zürich, the National University of Singapore, and the Singapore-ETH Centre. Your work will tie in closely with Singapore's Digital Underground programme. Prof. Dr. Konrad Schindler at D-BAUG ETH Zürich is primary advisor to this position.
The duration of the appointment is two years.
Please note that the employment will be at the Singapore-ETH Centre and local working regulations will apply. Workplace is Singapore.
Your key responsibilities will be to:
- Specify a software system for asset detection.
- Implement and test asset detectors, and collect training data for machine learning.
- Implement and adapt geometric fitting, modelling and measurement software for assets.
- Build prototype software for deployment with a real scanning system.
- Work with industry partners on the use and integration of available off-the-shelf components.
- Participate and contribute to the team’s weekly and monthly meetings and other interactions with key stakeholders from Singapore government agencies.
We offer you:
- An opportunity to do impactful work on a globally relevant issue.
- Ample opportunity to test and validate your work in the real world or with real-world data, based on already well-established connections with local Singaporean government agencies, contractors and technology providers.
- A clean, modern, and progressive work environment with competitive compensation commensurate to your skills and expertise.
- A diverse and interdisciplinary cast of colleagues, with plenty of opportunities to interact and collaborate with researchers from fields such as architecture, urban planning, social science, civil engineering, geomatics engineering, and computer science.
You can demonstrate that you possess the following:
- Experience and an academic degree (PhD preferred) in computer science (machine learning, computer vision, computer graphics) or related fields like robotics or geomatics.
- A solid background in engineering and mathematics.
- Programming skills, ideally in Python and/or C/C++.
- Experience in working with 3D point cloud data.
- Experience with machine learning and/or computational geometry.
- The capability to organise your own work and to solve problems independently.
- Fluent English and very good communication skills which you apply comfortably and proactively.
We look forward to receiving your online application with the following documents: a letter of motivation, a CV, electronic copies of your academic diplomas and certificates, and contact details for at least 2 referees. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Further information about the Digital Underground project and Singapore-ETH Centre can be found on our websites www.digitalunderground.sg and www.sec.ethz.ch. Questions regarding the position should be directed to Mr. Rob van Son, email firstname.lastname@example.org (no applications).