Complexity and causality in measured multivariate time series

PhD study program: Measurement Technology
Academic year: 2023-2024
Advisor: RNDr. Anna Krakovská, CSc. (anna.krakovska@savba.sk)
External educational institution: Institute of Measurement Science SAS
Accepting university: Faculty of Electrical Engineering and Information Technology, Slovak University of Technology in Bratislava, Institute of Electrical Engineering

Annotation:

The topic concerns the modern analysis of measured data. The emphasis will be on the development of causal detection methodology, taking into account the nature of the investigated processes (stochastic, fractal, deterministic, or combined). Among the investigated problems will be the evaluation of complexity of driving and driven systems. One of the goals of multivariate causal analysis will be to find the variables with the strongest influence, representing the most useful source of information. Diverse application areas include, for example, multi-channel electroencephalographic recordings from the human brain, multi-lead ECG measurements, extensive sets of climate measurements, time evolution of a set of macro-economic indicators and other real-world problems of finding causal relationships in measurements.

The thesis topic is suitable for a candidate with an interest in developing relevant mathematical approaches. Good English skills and experience in creating and testing software in the MatLab environment are also a necessary requirement. As part of the doctoral study, the student will expand his/her knowledge in the field of biomeasurement and get acquainted with methods from the theory of dynamical systems, including chaos and fractal theory and partly on statistics, information theory and mathematical optimization. The dissertation will be solved at the  Institute of Measurement Science of the Slovak Academy of Sciences in Bratislava.

 

More information about the project:

The project is funded within the European Doctoral Network for Neural Prostheses and Brain Research (DONUT), EU-Horizon Europe Marie Sklodowska-Curie Doctoral Network project that is aimed to bring together leading experts from several European universities with the mission to provide a multidisciplinary and intersectoral Doctoral Network for talented young researchers (Doctoral Candidates). The network connects leading scientists and institutions with several industries over different research fields, providing opportunity for young researchers to gain experience in translational research in electroencephalography (EEG)-based measurements and Brain-Computer Interface (BCI) applications, healthcare, and industry.

 

Detailed information on admission conditions is published on: https://euraxess.ec.europa.eu/jobs/183375