TITLE OF POST: Post Doctoral Researcher in Computational Social Science
LOCATION: MACSI at University of Limerick
SALARY SCALE: €37,874 - €49,048 p.a. pro rata
Informal queries: Prof James Gleeson
Further information for applicants and application material is available online from: http://www.ul.ie/hrvacancies/
CONTRACT TYPE: Specific Purpose
OVERALL PURPOSE OF THE JOB:
The Mathematics Applications Consortium for Science and Industry (MACSI) is Ireland’s largest applied and industrial mathematics group and works closely with scientists and industrial companies across a wide variety of sectors. MACSI’s aim is to foster new collaborative research, in particular on problems that arise in industry through the application of cutting-edge mathematical and modelling techniques.
The emerging discipline of Computational Social Science (CSS) studies human behaviour, as manifested in the digital trails we leave in our interactions with each other. The development of mathematical models for CSS is urgently required to underpin the analysis of large-scale data, and to move beyond the identification of correlations to create new scientific understanding of collective behaviour in both online and offline social networks.
In this Science Foundation Ireland funded project we are seeking to recruit a Post Doctoral Researcher to join Professor James Gleeson’s team in the development new mathematical techniques and models to help revolutionise the understanding of the dynamics of social spreading phenomena, such as viral information contagion and cascades of popularity. We will focus on the mathematics of age-dependent (non-Markovian) branching processes to generate analytical and asymptotic results for inference and calibration with large-scale CSS data. Understanding and controlling the temporal aspects of information diffusion and cascade dynamics on social networks will improve the predictability of technology adoption and opinion propagation, and enable us to accurately identify the most influential nodes within diverse dynamical systems on complex networks. Our algorithms will be applicable to online marketers, mobile phone networks, and in cases where widespread broadcasting public-interest information is urgent (e.g., health or terrorism alerts, missing-person searches, disaster relief).
Research Outputs - Write Up and Dissemination