Project Overview

Are you enthusiastic about building applications that make an impact? Be part of a world-class team working to protect forests and prevent transboundary smoke haze. We are a small, collaborative group in which you will be exposed to and learn from engineers and scientists from MIT, Stanford, NUS, and NASA while building code to predict the risk of peatland fires and transboundary smoke haze.

Responsibilities

We are seeking two Research Interns.

1.  Research Intern in Peat Fire Forecasting

You will work with us on forecasting fire risk in tropical peatlands of Sumatra using data assimilation and a simple hydrologic model.  This research is part of a larger collaboration between National University of Singapore and the Singapore-MIT Alliance for Research and Technology to predict fires that cause transboundary smoke haze in Singapore.  The successful applicant will work with our team to develop a prototype hydrological forecasting application using data assimilation and related statistical methods and contribute to analysis of field and remote sensing data.  Applicants ideally will have some familiarity with linear algebra and basic programming in a language such as Python.  Exposure to Bayesian inference, in particular data assimilation, is a plus.

2. Research Intern in Remote Sensing Data Assimilation

You will work with us on analysing radar and thermal imaging satellite data from the peatlands of Sumatra.  The data will be assimilated into a simple hydrologic model as part of a collaboration between National University of Singapore and the Singapore-MIT Alliance for Research and Technology project to predict fires that cause transboundary smoke haze in Singapore.  The successful applicant will work with our team to automate the extraction and analysis of hydrologic data from precipitation, soil moisture and surface temperature remote sensing products as part of a prototype hydrological forecasting application.  Applicants will have had some exposure to remote sensing and basic programming experience in a language such as Python.

Requirements

Bachelor students in software engineering, remote sensing, earth science, or a related field.

Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.