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EOS is a University Research Institute at Nanyang Technological University that conducts fundamental research on earthquakes, volcanic eruptions, tsunamis, and climate change in and around Southeast Asia, towards safer

and more sustainable societies. For more information on EOS please visit http://www.earthobservatory.sg.

The Air Pollution and Health team's research of Prof. Steve Yim focuses on the interactions between climate and air quality, and the resultant impacts on public health and ecosystem. The team's ongoing research is to develop, advance and utilize the state-of-the-art multi-scale atmospheric models, along with measurement and statistical approaches, to understand the mechanisms that drive the climate-air quality interactions, and evaluate the impacts on human exposure, mosquito abundance and soil acidity.

Particular interests are in investigating air quality impacts of sectoral emissions and transboundary air pollution at multiple spatial scales, studying regional climate change due to land-use changes and global climate change, and evaluating and quantifying the effects of air pollution on respiratory and cardiovascular diseases. The team also assesses and develops emission control scenarios to provide scientific-based policy solutions for a sustainable environment in present and future years.

Key Responsibilities:

The position will be required to develop and apply modeling techniques to simulate the spatial distribution of air pollutants in a city at a high spatial resolution. The model development requires to collect data at different aspects. The position will have to work on the data collection, data processing, model development and application, and data analyses. The position has to document the model development and results in reports and peer-review international journals. The position will also have to complete tasks that his/her supervisor assigns.

Job Requirements:

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  At least a Masters degree in atmospheric science/geography/meteorology/environment

  
  


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  To have experience in development of spatial models especially land-use regression model or machine learning

  
  

EOS seeks a diverse and inclusive workforce and is committed to equality of opportunity. We welcome applications from all and recruit on the basis of merit, regardless of age, race, gender, religion, marital status, family responsibilities, or disability.

We regret that only shortlisted candidates will be notified.