PhD Candidate on ’Predictive model for local urban climate using machine learning’

WorkplaceZurich, Zurich region, Switzerland


The Chair of Building Physics of ETH Zurich is performing multiscale research on the urban climate. In collaboration with the Laboratory of Multiscale Studies in Building Physics of Empa, we are recruiting a

PhD candidate on "Predictive model for local urban climate using machine learning"

We are looking for a highly skilled and motivated candidate that will that will study the urban climate and heat island effect for current and future climates. Due to the urban heat island effect, the air temperatures in urban areas are higher compared to their surrounding rural areas, especially during heat waves. To implement effective UHI mitigation measures, cities need to better understand their urban climates and the mechanisms causing local hotspots within their urban environments. Mesoscale climate simulations with an urban parametrization allow to model the urban climate, however at a high computational cost. Therefore, the student will develop and train a predictive model for local urban climate using machine learning of large simulated data. This predictive model will then be used to analyse the causes of local heat islands and the student will develop a methodology to propose adequate mitigation measures.

The candidate should be a responsible and communicative scientist with a master degree in mechanical, civil or material engineering, physics, computer science, materials science, or similar field. Optimally, the candidate should have a strong background in computational science, fluid dynamics as well as climate simulation. Previous experience in machine learning is highly desirable. The candidate should be proficient in English.

In your application, please refer to
and reference  JobID 38984.

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