The Dutch Network Science Society Young Talent Prize
The Dutch Network Science Society Young Talent Prize is awarded to an early-career talent in Network Science. Nominees will be evaluated for one (or more) specific accomplishment. The evaluation (jury led by the steering committee and board of the Dutch Network Science Society) will follow the guidelines stated in the new position paper on recognizing and rewarding academics by VSNU, which allows for diversification of excellence to include not only scientific quality, but also accomplishments in the domains of education, impact and leadership.
The Young Talent Prize comprises the opportunity to present at the Dutch NetSci Symposium 2020 and an official award.
Candidates should meet the following conditions:
• the candidate must have at least a Master’s degree;
• if the candidate is a doctor, the PhD degree should have been obtained within three years before April 29th 2020 (i.e. PhD defense after April 29th 2017);
• the candidate should be a member of the Dutch Network Science Society at the time of nomination (read here what our free membership entails);
• the accomplishment must be related to network science and should be achieved when the candidate is/was affiliated with a Dutch University.
When (deadline extended)?
Apr 29thAugust 31st 2020: aggregation of nominations.
September 15th 2020: decision by the award committee.
June 2nd 2020 Autumn 2020: Dutch NetSci Symposium 2020, where the awardee will be given the opportunity to present their work.
Applications should be submitted by the candidates themselves (via email@example.com) and must include:
• a 200-word narrative (in English) in pdf format on the candidate’s eligibility for this award, i.e. a description of the relevant accomplishment(s) in network science;
• an up-to-date CV in pdf format, optionally containing URLs to external material deemed relevant (e.g. PhD thesis, scientific article, popular scientific materials, educational innovation, etc);
• contact information (email and phone number) for at least one reference.
PhD student or Postdoc position at University of Amsterdam: Networks and value chains in organized crime
We are seeking a researcher (PhD candidate or Postdoctoral researcher) for a computational network science position to work on an exciting research project in an interdisciplinary team. You will focus on the use of mathematical and computational methods to study the organizing principles and adaptative, bottom-up nature of the various types of networks and value chains underlying modern organized crime activities.
There is a growing consensus that the complexities underlying crimes and criminal organisations cannot be unravelled by traditional methods alone. A shift in research paradigm to complex adaptive systems and network thinking is therefore imperative to move this field forward. Organized crime is a complex interplay between social networks, financial networks, communication networks, trust, opportunity, among others. A complex systems approach that studies these pathways, how these pathways adapt, and their interactions can support analysts and investigators in effectively tackling undermining criminal activities in a strategic manner.
Particularly novel in this project is that multiple rich intelligence datasets (anonymised) will be combined in order to create large, multiplex networks surrounding criminal activities. This quantitative data will be combined with qualitative knowledge from domain experts. The resulting networks (and value chains) will be conceptualized as a dynamical system which are adaptive and decentralised. The goal is to model, mathematically and computationally, the process of formation and evolution of the networks and value chains therein, and subsequently to use complexity science concepts to study the function of the emergent network topology as a resilient, bottom-up infrastructure for information, money, and commodities.
For more information about this position, please click here.
PhD student position at Eindhoven University of Technology
At Eindhoven University of Technology, shared between the Electrical Engineering and Mathematics and Computer Science Departments, there is a vacancy for a PhD student. The intended supervisors are George Exarchakos (EE) and Remco van der Hofstad (MCS). The project will focus on distributed ways to measure centrality in networks, for example using the Game of Thieves protocol. In this protocol, several walkers run through the network looking for commodities, and, upon finding them, the commodities are moved to the starting point of the walks. The most central nodes are the ones that receive the least commodities. The aim of the project is to describe this centrality measure, possibly using local weak convergence techniques, as well as to study what happens when central nodes are being removed. We are also interested in the dynamical properties of this centrality measure, in particular what happens when the graph changes over time while the walkers run around on the network.
We aim to approach these problems in a mathematically rigorous way, and we expect the candidate to have some experience in formally proving results. Some experience with simulations is welcome, though not required.
These questions are spurred by modern communication. Future communication networks are expected to be ultra dense in space and pervasive to our living spaces enabling far better coverage and higher bandwidth anywhere. Smart radio environments will play an important role to achieve this goal. Yet, their control has to become inherently distributed, autonomous and intelligent. The controllability of wireless mesh networks heavily depends on the properties of the graphs they form and their ability to coordinate in a local way. New intelligent methods are needed to achieve self-awareness of large-scale random wireless networks and to estimate the impact of a topology change. This project will study the fundamental models needed to achieve intelligence embedded at the nodes of the network.
This PhD project is within the NETWORKS Gravitation program NETWORKS, and the student will be expected to actively participate in this program.