Sub-network analysis for protein interaction networks using projection methods - how do we account for what we don't know? (Marie Curie Network position, 45k Euro/year gross)

The European network "Statistical Physics Approaches to Networks Across Disciplines" (NETADIS) is looking to recruit excellent Early Stage Researchers (ESRs) for attractively funded three-year PhD research projects at 9 leading European partner institutions. This position at King's College London should be taken up on 1 September 2012 or as soon as possible thereafter. Applications arriving after 15 March will be considered where possible.

Candidates are eligible to apply if they have an excellent first degree that qualifies for PhD study in a relevant discipline (e.g. physics, mathematics, computer science, engineering) with preferably a strong background in statistical physics, and less than four years of research experience. At the time of recruitment they must not have resided or carried out their main activity in the U.K. for more than 12 months in the last 3 years.

NETADIS aims to train a cadre of future research leaders in advanced methods of analysis, inference, control and optimization of network structure and dynamics, to maximize the impact of statistical physics approaches across a broad range of application areas. It is funded by the EU Marie Curie Actions. Each NETADIS project is defined by a research theme (inference; dynamics; optimization and control) and an application domain (systems biology and neuroscience; information technology; socio-economic systems and finance; network phenomena in physical systems).

Even for well-studied protein interaction networks in systems biology, like those of signalling receptors with a key role in cancer, much uncertainty remains: we cannot assume that the entire network is known.
Even if it were, analysing the dynamics mathematically requires restricting attention to a small enough sub-network. This project will study what can then be said about the dynamics on the known part of the network. It will exploit projection techniques from statistical physics, which focus from a large system down to a smaller set of observable quantities. We will also explore the reverse direction: can statistical inference be used to infer from observations of the sub-network dynamics something about the unknown network parts?

Training will be provided via local training courses, two targeted secondments to another network participant of 2-3 months length each, a scientific network kick-off meeting, two summer schools, and a final conference. ESRs will also receive training in transferable skills such as presentation skills; entrepreneurship and exploitation of results; and communication and outreach.