Network Epidemics Group @ Rényi Insitute

The Network Epidemics Group (https://renyi.hu/en/activities/kutatocsoportok/network-epidemics-group) at the Rényi Institute works on the mathematical, computational, and data-driven modelling of dynamical epidemiological processes on graphs and networks. On one hand, the group plays special focus on the mathematical foundation of geometric network effects on evolving spreading processes, and on the other hand, on the data-driven simulations of epidemic processes to observe and understand real-world spreading phenomena. The group is led by Prof. Márton Karsai and functions as a member of the National Laboratory for Health Security in Hungary.

Epidemic Modelling Group @ Bolyai Insitute

The research group (http://www.math.u-szeged.hu/~rost/researchgroup.html) at the Bolyai Institute works on the modelling of biological dynamics, mostly using analytical and numerical tools of nonlinear dynamical systems. The group works on a variety of problems in mathematical epidemiology. By disease modelling we can provide important information to public health by designing, evaluating and comparing different strategies to control the outbreak. The group is led by Prof. Gergely Röst who is also the PI of the National Laboratory for Health Security in Hungary.

Mission

It is a fundamental question in disease modeling how the structure and dynamics of social interactions and mobility mixing patterns influence an ongoing epidemic. These behavioral patterns can be effectively represented as networks, that provide effective tools for the mathematical and computational modelling of epidemic phenomena. They contribute to a better approximation that incorporates non-homogeneous mixing patterns within and between populations, which can build up into meta-population networks to describe how epidemics spread in countries or even around the globe.

The geometric structure and spatial organization of interaction and mobility networks play special roles in the emergence of a rich but largely unexplored set of spreading phenomena. One of these phenomena is the commonly observed spatial clustering of infection cases during the sub-sequent waves of the actual COVID-19 pandemic. While these phenomena can be related to the inhomogeneous spatial distribution of susceptible populations, local patterns of herd immunity or the different seeding scenarios of an actual wave, their emergence is substantially depending on the geometric nature of the underlying social and mobility networks.

In this project we aim to tackle this problem from two different directions:

• Computational modelling of epidemic processes on geometric networks: to develop a spatially embedded meta-population framework, relying on data from Hungary, that is capable to reproduce rich class of spatially clustered patterns of infected cases in the country.
• Mathematical modelling: to develop the mathematical foundation of these observed phenomena by identifying the fundamental graph properties of the underlying network structures that can induce the observed geometric patterns of infection clustering.

Job description

The successful applicant will work in the Health Security National Laboratory project under the supervision of Pr. Márton Karsai and Pr. Gergely Röst in the Rényi Institute of Mathematics in Budapest and the Bolyai Institute of Mathematics in Szeged. The successful candidate will work on the following tasks:
• Develop computational and mathematical models of epidemic processes on geometric networks.
• Participate in scientific publication writing and other types of dissemination.
• Participate in the scientific reporting of the project.
The candidate is expected to apply to the Doctoral School of Mathematics at the University of Szeged, and will be expected to fulfill all academic requirements requested by the School to obtain a PhD degree.

Skills and profile

Applicants should have a MSc degree in physics, mathematics, applied mathematics, statistics or computer science with some background in network science and/or dynamical processes. Background in computational modelling and formal methods is an advantage. Good academic writing, communication and presentation skills in English are required.

Benefits

The doctoral candidate will work in a truly international environment as a member of Europe’s leading centers in mathematics within a large project providing opportunities for further scientific interactions. The investigated topics are at the forefront of applied mathematics giving the young researcher a solid basis for her/his further career.

Additional information

Location:
• Rényi Institute of Mathematics, Budapest, Reáltanoda utca 13-15, 1053 Hungary
• Bolyai Institute of Mathematics, Szeged, Aradi Vértanúk tere, 6720 Hungary
Duration of the contract: 4 years
Expected date of start: September 2023