The position is in a project “Echo Chambers, Experts and Activists: Networks of Political Communication (ECANET)” funded by the Academy of Finland. The idea is to analyse how network roles and mechanisms related to polarisation work when they are taken out of isolation and multiple networks are considered at the same time. For example, are the polarisation mechanisms in social media amplified or dampened by what the traditional media does? Is there differences between countries in this? Our interdisciplinary team including experts on policy networks (University of Helsinki) and media studies (University of Tampere) will use data analysis and modelling approaches to study this type of questions. As a methodology we will use multilayer networks, and the concrete case we are interested is discussion on climate change in several countries. The project is running for 4 years between 2019-2022.
– Access to data and expertise related to project and otherwise
– Freedom and support to pursue your own research ideas (also outside of the project)
– Great place to work in an international research group
– Decent salary (currently standard postdoc salaries are around 3500-3700 EUR per month before taxes)
You should have:
– Solid background in network science and analysis of network data
– Programming skills needed to do simulations and data analysis (we mostly use Python/C++)
– Interest to work in an interdisciplinary project together with social scientists
– Interest towards multilayer networks and other topics of the project
It is considered a bonus if you have:
– Experience extracting and working with Twitter data
– Experience in multilayer networks
– Knowledge of climate change politics, policy networks, media studies or other topics of the project
To apply just email me at mikko.kivela (at) aalto.fi. You can include a CV if you have one ready, but don’t let it stop you if you are still working on it. I will arrange Skype interviews with candidates as applications come in.
|Duration/Period||2019 - 2022|
|Keywords||multilayer networks; network models; climate change; polarisation;|
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