The Environmental Solutions Initiative is currently hiring MIT students for the following positions:

Nature Based Solutions Program

ESI’s Nature Based Solutions Program is looking for two undergraduate students for our flagship research project focused on monitoring climate risks in Mocoa, Colombia, in collaboration with local partners including the Ministry of Environment and Sustainable Development; Corpoamazonia, the local environmental regulator for the Colombian Amazon; and the Development Bank for Latin America CAF.

Mocoa is a city located in the Amazon piedmont that suffered a devastating landslide in 2017 that affected around 40% of the city. The project aims to provide an effective and robust landslide monitoring system that uses data collected by Unmanned Aerial Vehicles (UAVs) to develop an innovative algorithm using machine learning and artificial intelligence to model and predict landslide probability and risk mitigation scenarios, while strengthening the capacity of local authorities and communities to participate in risk management through a participatory research and a public engagement process. Moreover, a publicly accessible decision support web tool will be developed for interactive visualization of results for scenario planning, risk assessment, and to inform local adaptation strategies.

The project provides a learning context in which students can develop technical skills needed to map, monitor and predict climate risks, while engaging in community participation and communications strategies that effectively increase community resilience. The research will be supervised by ESI’s faculty director, Prof. John E. Fernández, with the support of teams at ESI and Lincoln Labs.

  1. The first position will assist with machine learning development, designing and implementing a methodology to analyze and predict landslide probability from Lidar point cloud data. Activities include creating a framework for a systems-level coordination of lidar data collected through drones, building and updating a dynamic dataset and a parameter library to act as a custom training dataset for current and future algorithms, and developing and executing and an unsupervised AI algorithm that runs in real-time to assess the probability that establishes key factors in land displacement. Requirements for this position include:
    • Course 6 major
    • Experience in Computer Vision and Deep Learning using Neural Networks with special emphasis on geometric data
    • Experience with 3D Convolutional Neural Network, LSTM Recurrent Neural Network and Bayesian Inference, and Probabilistic models is preferred
  2. The second position will assist with spatial analysis, visualization and risk communications. We are looking to engage a student with advanced capacity to analyze and synthesize complex and technical information to support the community engagement process with the goal of establishing a dialogue between vulnerable communities, private companies, and local planning authorities. This includes activities such as the development of maps and visualizations to communicate risks to diverse audiences, the development of factsheets and infographics to describe data collection and analysis processes, and participation in the design of a wireframe for an online decision support tool for risk scenario planning. Requirements for this position include:
    • Experience or interest in urban planning, urban design or related design fields.
    • Experience or interest in spatial analysis and GIS software
    • Experience working with data visualization, and familiarity with Adobe Creative suite
    • Verbal and written fluency in Spanish is preferred

The positions will be remote. Students are expected to work between 5 and 10 hours per week during the Spring semester. The students will receive a stipend up to $1,900.

To apply for either of these positions, email a resume to Marcela Angel at