Queen Mary, University of London is one of the world's leading universities (in the top one per cent of universities in the world according to the Times Higher Education). We have an impressive reputation for academic excellence, reinforced by our membership of the Russell Group of leading UK universities, which helps us to attract some of the brightest minds to study, teach and research here. We work across the humanities, social sciences, law, medicine and dentistry, and science and engineering. We are based in a creative and culturally diverse area of east London and are the only London university able to offer a completely integrated residential campus at our Mile End home.The School of Mathematical Sciences is one of the largest UK mathematical science departments and is one of five Schools in the Faculty of Science and Engineering at Queen Mary. The School offers energetic and diverse postgraduate activity across the spectrum of mathematical sciences from pure and applied mathematics to statistics. Our staff includes international leaders in many areas of mathematical research, and the School is a hive of activity, providing a vibrant postgraduate life. For more information about the School please see www.maths.qmul.ac.uk/
We have one opening for a 30-months Postdoctoral Research Assistant position to work on complex networks. This position is funded by the EPSRC project GALE (Global Accessibility to Local Experience) to carry out research on complex networks 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 firstname.lastname@example.org
Project details: GALE is an interdisciplinary project involving Complex Networks (QMUL), Computer Science (University of Cambridge), and Urban Design (University of Strathclyde). The main motivation behind the project is to pioneer a new generation of recommender systems which would make it possible for the rapidly growing population of global city users to access, in real time, a level of information, that of the neighborhoods knowledge, which is inherently inaccessible to global repositories.The research hypothesis behind GALE is that, with a new scientific definition of neighborhoods and the use of geo-social network metrics on data harvested from mobile phones and online social networks, it is possible to build recommender systems which are more like a local human guide than a book guide, and can therefore deliver better integrated socio-geographic recommendations, offering the local experience of places in real-time to everyday city-users as well as to the growing cohort of external visitors. To support our research hypothesis we will explore a notion of “fluid neighborhood” that is constructed in society (socially and culturally, individually and collectively) like the one used by environmental psychologists and urban sociologists, but still identified in space (geographically), like the one used by urban designers. Secondarily, we will envision how the evidence generated about fluid neighborhoods' nature and behavior may change the way we understand the life of urban communities, the way they interact with space, the way we can govern and plan them, and how these dynamics may be shaped by the future evolution of technology. The tangible output of the GALE project will be a next generation recommender system at the interface between the social and geographic dimensions of people activity in space and time. The recommender system will be accessible by personal mobile computing devices, and will allow people to orient themselves in local neighborhoods and benefit of local neighborhood-specific information in real-time.
The successful candidate will be expected to have a PhD 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.
The position is supported by the EPSRC project GALE (Global Accessibility to Local Experience). This full time, 30 months fixed term position is available to start on 1 July 2013, or as soon as possible thereafter.
Starting salary will be Grade 4 Research £30,805 - £34,283 inclusive of London Allowance. Our excellent benefits package includes:
• 30 days' annual leave and defined benefit pension scheme.
• interest-free season ticket loan and cycle to work scheme.
• discounted membership of the university gym and free use of university libraries.
• a wide range of family friendly benefits, including the university's own nursery.
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.
To apply, please visit the Human Resources website on http://www.hr.qmul.ac.uk/vacancies and search for reference QMUL2079.
Please ensure you include with your application a curriculum vitae, a list of publications and a research statement.
The closing date for applications is 8 July 2013. Valuing Diversity & Committed to Equality