We have one opening for a 3-years postdoctoral research associate position to work on complex networks. This position is funded by the EU FP7 project LASAGNE (multi-LAyer SpAtiotemporal Generalized NEtworks) to carry out research on multiplex networks, i.e. networks with multiple types of connections, and embedded in space and time. The research will be both analytical and computational, and will focus on developing a coherent theoretical framework for such systems and on the validation of the theory on real-world applications. We are looking for people with a strong background in complex networks, scientific computing and with good communication skills. For further enquires please contact Prof. V. Latora email@example.com
Project details: Thanks to modern ICT, a new generation of large datasets of social, biological, and man-made systems is now available. Such data contain high precision and integrated information on the nature and the evolution, in space and time, of the state of each single component, together with information on different types of interactions between them. Unfortunately, it is extremely difficult to extract meaningful information from this new generation of high-integrated data, since current network theory provides not much more than a static description of single, independent networks. The aim of this research project is to provide a coherent theoretical framework for analyzing and modeling these dynamic and multi-layer networks in terms of multi-graphs embedded in space and time. To do this, we will treat time, space and the nature of interactions not as additional dimensions of the problem, but as natural, inherent components of the very same generalized network (GNE) description. The first goal of the project is to devise novel metrics and models, able to capture the interactions between different layers and across different spatio-temporal scales. The second goal is to understand the combined role of spatial distance, time and inter-layer interactions on the dynamics of processes running on GNEs, and on the emergence of collective behaviors, such as synchronization. The third goal is to investigate cases where GNEs are co-evolving with the processes they facilitate. The project will be highly inter-disciplinary and combine analytical approaches and computational methods. The theory will be validated on real-world applications involving large and heterogeneous data sets of brain networks, on- and off-line social systems, healthcare systems, and transportation flows in cities.
Suitable candidates: The successful candidate will be expected to have a PhD or equivalent in mathematics, applied mathematics, computer science, physics, statistics, or a closely related discipline. The successful candidate should also have a strong background in complex networks, and experience in computational modeling and analysis of large-scale complex systems.
Candidates must be able to demonstrate their eligibility to work in the UK in accordance with the Immigration, Asylum and Nationality Act 2006. Where required this may include entry clearance or continued leave to remain under the Points Based Immigration Scheme.
This full time, 3 years fixed term position is available to start on as soon as possible. Starting salary will be Grade Research 5, sp. point 31 £33,944 inclusive of London Allowance. Benefits include 30 days annual leave plus 4 College closure days, defined benefit pension scheme and interest-free season ticket loan.
For more information about the School please see www.maths.qmul.ac.uk/.
Informal enquiries can be made by email to Prof. V. Latora firstname.lastname@example.org.
Please ensure you include with your application, a curriculum vitae, a list of publications and a research statement.
To download the application form and to apply for this position, please follow the link http://www.jobs.qmul.ac.uk and search for reference number QMUL1340.
The closing date for applications is 5th December 2012.
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