Stockholm Environmental Institute (SEI) is an independent, international research institute founded in 1989. Its mission is to support decision-making and induce change towards sustainable development by providing integrative knowledge that bridges science and policy in the field of environment and development. SEI is ranked as the second most influential environment think tank in the world in the Global Go To Think Tank Report, compiled by the University of Pennsylvania's Think Tanks and Civil Societies Program. SEI has about 220 employees in seven centres around the world.
SEI Oxford, a UK based, not for profit centre and subsidiary of the SEI Foundation, has specific expertise working on bridging climate change adaptation and disaster risk reduction; systematised knowledge exchange and learning; adaptation decision support; institutional strengthening; knowledge brokering and learning; capacity building; transparency of climate action and finance; institutional complexity in climate governance; policy analysis with an EU focus; climate and trade and energy innovation policies. SEI Oxford has a reputation for working at the interface between the natural and social sciences, undertaking research, and developing tools and methods of analysis to directly support the decisions and operational work of partner and donor organisations with an emphasis on the co-creation of knowledge. The scale of analysis and audiences is broad: from institutional engagement to user engagement and from policy analysis and impact to practitioners and communities.
The research assistant will work on data analysis, visualisation and decision support design on tasks across different projects and application areas.
This is an opportunity to work with different staff members in a multidisciplinary team to learn about the research processes involved, working on climate change and sustainable development issues to contribute to different data visualisations/data products and decision support methodologies.
Tasks: These tasks involve data analysis, including visualisation (Gephi, UCINET), statistical analysis (Excel, R, Python or others), text analysis/data mining (Python/R), development of tools/products guidance and documentation and design and development of decision support methods. You will be expected to help us analyse empirical data or to work on your own data sources.
Applicants should be comfortable working with all types of qualitative and quantitative data: social surveys, big data, geographic data, simulation data, etc.