WE SEARCH FOR
The successful candidate will conduct research in the area of network science of crime and will develop statistical methods and simulation tools that can be used for strategic analysis of networks in the context of crime. He or she will evaluate existing and develop new innovative (AI) tools from data, network, and complexity science to understand the organization and social interactions of crime. This includes work on interactive graph analysis networks, use of graph data for research purposes, research and evaluation of existing AI solutions, method development and the analysis of big data.
YOUR PROFILE
We are looking for an excellent young scientist with a Master’s degree (or equivalent) with a quantitative focus (e.g. data or network science, physics, mathematics). In your Master’s thesis, you have successfully shown your quantitative research skills. You have the ability to independently carry out data-intensive research and show good programming (e.g., Python, R, Julia), modelling and quantitative skills. Knowledge of data transformation and orchestration tools like DBT and Dagster are a plus. Proficiency in English (written and spoken). German skills are a plus. We search for critical thinkers that are open-minded, have a collaborative spirit and feel comfortable within an interdisciplinary environment cutting across network science, complex systems science and social network analysis.
WE OFFER
A fully funded 3-year PhD position in an exciting research environment at the Complexity Science Hub, close collaboration with colleagues from other research teams, access to a network of world-renowned researchers and a great community of talented, young, and motivated PhD and Postdoc researchers. The PhD will be supervised in the group of Stefan Thurner. The position is available as soon as possible.
We offer for this parttime (30h/week) Position € 37,557 gross/year.
About us
The Complexity Science Hub (CSH) is Europe’s research center for the study of complex systems. We derive meaning from data from a range of disciplines – economics, medicine, ecology, and the social sciences – as a basis for actionable solutions for a better world. Established in 2015, we have grown to over 70 researchers, driven by the increasing demand to gain a genuine understanding of the networks that underlie society, from healthcare to supply chains. Through our complexity science approaches linking physics, mathematics, and computational modeling with data and network science, we develop the capacity to address today’s and tomorrow’s challenges.
