Research Assistant – Extreme Citizen Science Group

The Extreme Citizen Science: Analysis and Visualisation (ECSAnVis) is a five-year, €2.5M project funded by the European Research Council, which aims to develop geographical analysis and visualisation tools that can be used, successfully, by non-literate people and any other community in culturally appropriate ways and in accordance with their needs. We currently work predominantly with indigenous communities in knowledge co-production practices to address problems and issues that are important to them, in some of the most critical environments on Earth.

The interdisciplinary Extreme Citizen Science (ExCiteS) research group is situated within the Department of Geography. The group was formed in 2011 by Prof. Muki Haklay (Department of Geography), Dr. Jerome Lewis (Department of Anthropology), and Dr. Claire Ellul (Department of Civil and Geomatic Engineering) as an interdisciplinary initiative to push the boundaries of citizen science to explore how we use and understand the world around us. More information can be found on http://www.ucl.ac.uk/excites. The group’s cross-cutting research on citizen science methods and technologies offer exciting opportunities for innovative research. 

The Research Assistant will work on the ECSAnVis project, primarily under the direct supervision of Dr Megan Laws. They will work with both the London-based UCL ExCiteS team and remotely with researchers and local assistants in Brazil, Cameroon, Ethiopia, Kenya, Namibia, and the Republic of Congo.  They will train and support existing and potential users of the group’s tools and methods, designing and developing training materials to support the needs of the various case studies and experiments.  

This is a fixed term, part time position (0.5FTE equal to 2.5 days/week), duration 12 months initially. Appointment to be taken up from May 2021 or as soon as possible. 

Key Requirements

The successful candidate will need to have a Masters or equivalent experience in digital antropology/similar (i.e.  involving both social/geographic science and digital technology). It is also essential that they have previous work or research experience in analysing data from case studies; knowledge of and interest in geographic citizen science and experience of using GIS software.