COSMOS (Complex Oscillatory Systems: Modeling and Analysis) is a three-year doctoral training framework for a European Joint Doctorate (EJD), training 15 early stage researchers (ESRs) at 8 top European Universities, in collaboration with 11 industrial and research partner institutions. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 642563.
In their projects, ESRs are co-supervised by partners in two different countries and undertake a one-year mobility period and a three-month industrial placement. Our goal is to, within the rigorous scientific framework of our projects, implement a bespoke program of excellent discipline-specific and transferable skills development.
The overarching research aim of COSMOS is to understand the behaviour of large and complex systems, specifically those composed of multiple interrelated sub-units, many of which operate on different time scales. The novel interdisciplinary approach proposed by COSMOS is to guide the characterization and data-analysis of intrinsically complex dynamics and systems with the help of skillful assumptions on the underlying mathematical models. Many real-world systems are indeed too complex, to allow for a blind extraction of information from raw data. COSMOS will pursue three main research objectives:
- The development of methods for the identification of the relevant variables (top-down approach).
- The extraction of the relevant information from multivariate-data recorded in complex oscillatory systems (bottom-up approach).
- Integration of the two approaches for cross validation and refinement.
- Implementation of the findings in software toolboxes for the use of unskilled users.
The COSMOS training will provide great versatility in our students; although ESRs will be mainly trained by working on specific problems (typically related to physiological or neural systems), the focus of the training will be more on the methods and tools rather than on the type of signals to be analysed. This kind of preparation will offer a much higher flexibility: competences in synergetic application of data analysis in combination with theoretical modelling can offer a wide range of opportunities in sectors like analysis of medical data, weather prediction, engineering, and analysis of social and financial data, power-grid, air-traffic, or neuroscience.