Traffic jams, dunes, water, ecosystems... All have in common being emergent phenomena resulting from the collective behavior of a large amount of interacting "particles" (cars, sand grains, molecules, species...). To understand them we need to integrate out details in terms of macroscopic variables. We refer to them as complex systems. They are characterized by selforganization at different leves, each with its own structures emerging from the previous level. Many of these systems have a strong socio-economic impact (e.g. traffic jams or stock markets) and others have very important technological applications (material science, lasers, oil industry, communications, biotechnology...). Hence the importance to understand them.

Complex Systems Science is has a strong crossdisciplinary nature because these systems usually do not fit within a single discipline (their microscopic elements and their collective phenomena often fall into different disciplines). The approaches to analyze complex systems are also diverse and with a strong statistical bias. Even though Complex Systems Science was born more than a century ago as Statistical Physics, it was the realization, at the end of the past century, that the same models it developed are able to account for phenomena typical from Sociology, Biology or Economics, that transformed Statistical Physics into the current Science of Complex Systems. Statistical physicists are, at present, crossdisciplinary by training, and are able to translate problems across disciplines as well as to deal with scientific problems at the border betwen disciplines.

With the aim at organizing and structuring this proposal into a few neat scientific goals, and paying attention to the nature and specialization of the groups involved, we have arranged the activity we plan to develop into three big research lines, which can be described as Modelling and Simulation of Condensed Matter and Complex Materials, Biological Systems and Processes, and Complex Networks and Social Behavior.