What do Facebook, the financial system, Internet or the brain have in common? "Everything is connected, all is network"
From the underlying skeleton of social relations, the interdependent evolution of our financial system, to the emergent collective computation in the brain, most of the complex systems that appear in society, technology, and nature are ultimately characterised by a nontrivial pattern of inter-relations. This underlying architecture is in turn shaping how information diffuses and spreads, how resilient the system is against attacks or perturbations, or how complex patterns emerge at the systemic level from the aggregation of seemingly simple individuals.
Our MSc Network Science will provide a thorough grounding in the core principles of modelling and analysis of complex and networked systems, along with the principal analytical and numerical methodologies. This will open to students a host of career opportunities in systems and networks modelling industries, spanning the IT, financial, and biomedical sectors, that are now requiring such specialist knowledge and skills.
Network Science is a very active and rapidly evolving research field with high societal impact, which stands at the crossroads of graph theory, complexity and data analysis. Addressing the description and modelling of the architecture and dynamics of complex systems -systems composed by many interacting units that show collective behaviour- it stands as a new kind of science to cope with some of the most challenging endeavours we face today, in an ever increasingly more connected society.
Its impact and applications outside academia pervades technological sectors such as communications and infrastructures (Internet, transportation networks, energy networks, urban mobility), finance (financial risk and systemic instability, financial networks, interbank cross-correlations), marketing and IT (social media, data analytics), public health (epidemic spreading models), or biostatistics and network biology (brain modelling, protein interaction networks, postgenomic era), to cite a few. This specialist masters programme aims at providing graduate students and professionals with a rigorous training in the underlying mathematical concepts, the analysis and modelling of complex networks and networked systems, complemented with training in computing, numerical simulations and massive data analysis. It is aimed towards students with a mathematical background who wish to enter a career involving analysis and optimisation of diverse kinds of networks, networked dynamics and models.
Why study your MSc Network Science at Queen Mary?
This is a pioneering MSc in the UK, a joint programme, taught by our Schools of Mathematical Sciences, and Electronic Engineering and Computer Science, drawing on their strengths in research and teaching in the area of complex networks, mathematical modelling of complex systems, and data mining.
We teach what we know and what we do best. Within the School of Mathematics, the Complex Systems & Networks group is one of the biggest hubs in Network Science within the UK, where we address both fundamental and applied challenges in the mathematical modelling of complex systems with clear societal impact, in collaboration with several industrial stakeholders. Within the School of Electronic Engineering, the Networks group was founded in 1987, and has hugely expanded ever since, bringing their expertise in online social networks, data mining and cloud computing. The coalescence of both groups expertises has fostered the creation of this unique MSc.
More about our two schools
Queen Mary is a member of the prestigious Russell Group of leading UK universities, combining world-class research, teaching excellence and unrivalled links with business and the public sector. The School of Mathematical Sciences has a distinguished history on itself. We have been conducting pioneering mathematical research since the 1950s, and as one of the largest mathematical departments in the UK, with over 50 members of staff, the school can offer diverse postgraduate study opportunities across the field, from pure and applied mathematics, to finance and statistics. Along with the MSc in Network Science, our cohort of postgraduate students specialise in Mathematics and Statistics, Mathematical Finance and Financial Computing. We are one of the UK’s leading universities in the most recent national assessment of research quality, we were placed ninth in the UK (REF 2014) amongst multi-faculty universities. This means that the teaching on our postgraduate programmes is directly inspired by the world-leading research of our academics. Our staff includes international leaders in many areas of mathematical research, and the School is a hive of activity, providing a vibrant intellectual space for postgraduate study.
The School of Electronic Engineering and Computer Science is internationally recognised for their pioneering and ground-breaking research in several areas including machine learning and applied network analysis. This expertise uniquely complements the more theoretical knowledge offered by the School of Mathematical Sciences, providing a well balanced mix of theory and applications and offering a deep and robust programme that combines the foundations of the mathematics of networks with the latest cutting edge applications in real world problems.
Additionally, Queen Mary holds a university-level Bronze Award for the Athena SWAN Charter, which recognises and celebrates good employment practice for women working in mathematics, science, engineering and technology in higher education and research.
You will be able to enjoy the facilities from two schools developing cutting-edge research. Within the Schoolof Mathematical Sciences, The Learning Resource centre has 200 networked PCs and is open to students round the clock, there are dedicated workstations for postgraduate students. You willhave access to specialised facilities and equipment, including:
• A large shared office in the Mathematics Building and a dedicated computer network.
• Access to a full range of computing facilities including a High Performance Computing Unit.
• Our library has about 8,000 mathematical books and subscribes to a large number of mathematical journals. There is also access to substantial numbers of electronic journals.
As a complement, the School of Electronic Engineering and Computer Science offers taught postgraduate students their own computing laboratory. MSc students have exclusive use of the top floor in our purpose-built, climate controlled, award winning Informatics Teaching Laboratory (ITL) outside of scheduled laboratory sessions. The ITL hosts over 250 state-of-the-art PCs capable of multimedia production and several laser printers. In addition, there are video conference facilities, seminar rooms, and on-site teaching services and technical support. There are also a number of breakout spaces available to students with full wi-fi access allowing you use your own mobile devices.
The ITL is primarily used for taught laboratory sessions and regularly hosts research workshops and drop-in lab facilities. For postgraduate students on taught and research degrees there are specialist laboratories to use for carrying out research. Our augmented human interaction (AHI) laboratory combines pioneering technologies including full-body and multi-person motion capture, virtual and augmented reality systems and advanced aural and visual display technologies. We also have specialist laboratories in multimedia, telecommunication networks; and microwave antennas. In addition to these spaces, PhD students have generous study space in our research laboratories. In 2011 we completed the £2m development of new experimental facilities in Antennas and Media and Arts Technology. We formed the Interdisciplinary Informatics Hub in Collaboration with the Schools of Biological and Chemical Sciences and Mathematical Sciences. These laboratories provided a meeting place for postgraduates from the three Schools to interact and exchange ideas.
You will also have access to Queen Mary’s comprehensive libraries, including the Postgraduate Reading Room, and The British Library can also be accessed as a research resource.