The Singapore-ETH Centre for Global Environmental Sustainability (SEC),
a joint initiative between ETH Zurich and Singapore’s National Research Foundation (NRF), launched the Future Cities Laboratory (FCL) as its first research program in Singapore in September 2010. The FCL undertakes cutting-edge research in disciplines ranging from planning, engineering, and environmental technologies to communication technology and architecture. The Big Data Informed Urban Design project lead by ETH Prof. Gerhard Schmitt, researches and develops methods and guidelines for integrating advanced data analytics into the urban design and planning process. In order to make data analytics available to design, the main task involves extracting information and knowledge from urban data and investigating correlations between spatial configurations and behavioural phenomena. In this context the FCL is announcing the following job opening:PhD Position for Cognitive Computing for Urban Planning
This project focuses on the analysis of how urban planners work and how they interact with computational urban planning tools. The goal is to create more responsive and adequate interactions between humans and computational tools. A key to natural interaction is the understanding what either humans or machines could do on their own. You develop tools that combine spatial intelligence, hypothesis generation and evaluation, and dynamic learning for a powerful, fast, and accurate urban planning solution. The work place is at Singapore-ETH Centre, CREATE Tower in Singapore. The position will be available from 1 September 2015.
The successful candidate has a Master degree in Computational Science, Mathematics, Statistics, or with equivalent relevant background, who is interested in working in an interdisciplinary environment at the interface of urban design and algorithm development for large-scale data analysis problems. Ideally you will have a strong background in computational design synthesis techniques and experiences with computational geometry, network analysis, deep learning and machine learning technologies. Applicants educated in architecture or urban planning are welcome, but need to prove their knowledge and experience in one of the above areas. Your English must be fluent, both written and spoken.
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