DNDS @ CEU
The Department of Network and Data Science (DNDS) at the Central European University (CEU) carries out research in network science, with a special focus on the foundations and applications of network science to practical data-driven problems. A key element of the mission of DNDS is to work across disciplines to bring network and data science tools to many fields of the social sciences and related areas. DNDS translates these ideas into research projects - our faculty have won several major grants, from European Union and US funding agencies. DNDS offers a PhD Program and an Advanced Certificate Program in Network Science and will host a BA in Quantitative Social Sciences starting, presumably, in 2021. Data science tools and the network science approach offer a unique perspective to tackle complex problems, impenetrable to linear-proportional thinking. Building on decades of development of fundamental understanding of networks, the modern data deluge has opened up unprecedented opportunities to study and understand the structure and function of social, economic, political and information systems. Data-driven network science aims at explaining complex phenomena at larger scales emerging from simple principles of network link formation.
Cities have become the economic bedrock of modern nations; in little more than a century they have gone from concentrating 13% to an estimated 55% of the world population, with 600 of them currently accounting for around half of the global economic output. This increased urbanization is a key driver of economic dynamism and social development, but it can also create enormous social challenges. The management of global medical emergencies, natural hazards and pollution, migration, the exclusion of the poor from the city’s socioeconomic fabric, and the surge of social and economic inequalities as well as the political consequences thereof are all concerns of modern urbanized population. Tackling these challenges is of paramount importance to fulfill the economic and social promises that cities hold, keeping them from becoming sources of social and political instability.
To answer some of these challenges, in this postdoctoral project we aim to tackle several problems related to socioeconomic inequalities and their consequences by targeting four inter-related questions:
• The inference and its transferability problems of socioeconomic status of people living in cities
• Effects of socioeconomic status on people’s social network formation and the characterization of social stratification and network segregation
• Socioeconomic patterns of mobility to explore signs of mobility segregations
• The effects of socioeconomic patterns in networks and mobility on spreading of social and biological epidemics
The successful candidate will work on the following tasks:
• Collection and/or curation of collected large digital spatial-temporal datasets for data-driven studies
• Analysis of mobility and social network datasets with advanced statistical and machine learning methods
• Modelling of human interaction and mobility dynamics
• Collaborative research with PhD students
Applicants should have a PhD degree in data science, computational social science, computer science, physics, or related discipline with strong interest in complex networks, social phenomena, and human dynamics. Background in complex networks, data mining, statistical analysis, computational modelling is expected. Efficiency in programming, data collection and analysis are required. Good academic writing, communication and presentation skills in English are required. There are no teaching obligations but opportunities.
We offer a competitive salary that is commensurate with experience as well as a dynamic and international academic environment. The initial contract is for one year and may be extended by one more additional year.
The postdoctoral fellow will work in a truly international environment as a member of one of Europe’s leading centers in network science within a large international project providing opportunities for further scientific interactions. The investigated topics are at the forefront of computational social science giving the young researcher a solid basis for her/his further career. Vienna has been for years at the top in the list of most livable cities in the World.
How to apply
Applicants need to submit:
• Brief statement of research interests
• Contact information of two references
Please send your complete application package to:
firstname.lastname@example.org - including job code in subject line: 2020/042.
Review of the applications starts June 30th and continues until the position is filled.
|Keywords||socioeconomic inequalities; mobility; and social networks;|
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