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Advanced Computational Methods for Uncertainty Analysis in Measurements
PhD study program: Measurement Technology
Academic year: 2024-2025
Advisor: doc. RNDr. Viktor Witkovský, CSc. (viktor.witkovsky@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 of the dissertation focuses on developing advanced computational methods for uncertainty analysis with particular focus on biomedical measurements, including but not limited to NMR, EEG, and ECG measurements. The research will address common sources of measurement uncertainty and investigate calibration methods to improve measurement accuracy and consistency. An important goal of the dissertation will be the design and use of advanced computational methods, including Monte Carlo methods and numerical inversion of the characteristic function of the associated probability distribution, for more precise and reliable uncertainty estimates in the field of biometrics. Successful completion of this research will contribute to the development of more robust and accurate measurement techniques in the biomedical field, which can ultimately contribute to improving diagnostic methods as well as patient treatment success. Basic knowledge of measurement principles, metrology, statistics, and machine learning methods, as well as good programming skills, are necessary prerequisites for this research. The student will conduct research at the Institute of Measurement Science of the Slovak Academy of Sciences in Bratislava, where they will have access to modern laboratory equipment and a motivating research environment. The student will also have the opportunity to participate in current research projects and be involved in international scientific research cooperation.