Employer: Rényi Institute of Mathematics

Place: Budapest, Hungary

Research theme: epidemic modeling, network science, graph theory, geometric networks, metapopulation models

Scientific directors: Dr. Márton Karsai (karsai.marton@gmail.com ) & Prof. Dr. László Lovász (laszlo.lovasz@ttk.elte.hu )

Network Epidemics Group @ Rényi Insitute

The 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 Dr. Márton Karsai and Pr. László Lovász and functions as a member of the Health Security National Laboratory 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.

Read the full article at: renyi.hu

This explorable illustrates beautiful dynamical patterns that can be generated by a simple game theoretic model on a lattice. The core of the model is the Prisoner’s Dilemma, a legendary game analyzed in game theory. In the game, two players can choose to cooperate or defect. Depending on their choice, they receive a pre-specified payoffs. The payoffs are chosen such that it seems difficult to make the right strategy choice.

Read the full article at: www.complexity-explorables.org

Frontiers in Complex Systems publishes rigorously peer-reviewed quantitative research on Complex Systems, either theoretical, experimental, mathematical, computational or data description. Field Chief Editor Maxi San Miguel at the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) in Spain is supported by an outstanding Editorial Board of international experts. This open-access journal is to become the reference and natural publication outlet for the Complex Systems community at large, and to be at the forefront of disseminating and communicating scientific knowledge and technological innovation in the field to researchers, academics, entrepreneurs, companies, policy makers and the public worldwide.

Frontiers in Complex Systems covers fundamental questions, theories and general methodologies on complex systems as well as the cross-disciplinary application of these concepts and methods, often giving rise to new disciplines. It provides a forum for cross-disciplinary communication and welcomes quantitative research from different fields including Physics, Mathematics, Computer Sciences, Artificial Intelligence, Engineering, Climate change, Economics and Finance, Social Sciences, Linguistics, Ecology, Neuroscience, Health Sciences, Epidemics, Mobility and Transport, City Science, etc. Submissions to Frontiers in Complex Systems are made to appropriate specialty sections, each of which devoted to a specific sub-field and having their own expert editorial board. Aligned with the cross-disciplinary scope of the journal, some of these sections are shared with other Frontiers journals, providing an enhanced visibility of the research in different scientific communities.

More at: www.frontiersin.org

FBK-CHuB is seeking a Researcher in the field of the classification, analysis and modelling of online disinformation spreading behaviour.
In particular, the candidate will be involved in a large European research project focused on the development of a platform tackling misinformation and disinformation across the EU by empowering scientific researchers and media practitioners with advanced AI-based technologies that: 1) allow multichannel (distinct online social media and news feeds), multilingual and multimodal (textual, visual and audio content) monitoring, detection and recording of misinformation and disinformation on online social media and traditional media; 2) estimate the risk of unreliable information consumption; 3) create a trustworthy online environment involving researchers, media practitioners and policy makers to facilitate the creation and distribution of reliable information and counter-narratives, while labelling and countering mis/disinformation.

Read the full article at: jobs.fbk.eu

You will produce a simulation program demonstrating self-organizing logistic networks that become more circular and sustainable over time. 

You will create novel research breakthroughs and contribute to the ambitious ERC Advanced Investigator Grant on “Co-Evolving City Life” (CoCi) in subject areas connected to smart cities and digital societies. Your research focus will be on “Sustainable Cities and Coordination”. Given recent digital technologies such as the Internet of Things (sensor and communication networks), Artificial Intelligence, and blockchain technology, one can expect that production, logistics, and even waste, are becoming increasingly smart. Ideally, you will study how the convergence of these technologies can be used to fuel new approaches towards more sustainable production and logistics in an urban context. 

The research question we would like to answer is, how the approach of self-organized and federated, learning, networked multi-agent systems can be used to create socio-economic incentives that would promote the emergence of closed loops in a material supply network and could thereby boost the formation of a circular and sharing economy. We want to study, how a multi-dimensional real-time measurement, feedback and coordination system would have to be designed and operated in order to reach this goal. 

Together with our team, you will work on the mechanisms and effects of multi-dimensional real-time coordination, perform related agent-based simulations, and work towards demonstrating the approach in an application project. It will be great to couple the simulation program with a sensor-based environment (Raspberry Pi or Arduino, or other) that responds to measurements, flexibly adapts, and self-organizes. You will be the key researcher addressing these challenges or a subset of them (please specify), collaborating with a highly motivated team.

More at: www.jobs.ethz.ch