DCCE offers a course TECHNICAL CYBERNSTICS in doctoral degree.

Doctoral studies are presumed for university graduates who have achieved a level of study corresponding to MSc.

Ph.D. students design their own individual plan of study that must list four courses suggested by the supervisor. These courses are compulsory. In addition, optional courses may be added to the plan upon the supervisor´s recommendation. During the initial two years of study, doctoral students attend lectures selected by their supervisors.

Selected PhD topics

Multivariate Statistics in Spatial Reconstruction of Cell Organelles Based on Fluorescence Microscopy (prof. Aleš Procházka)

Abstract: Fluorescence microscopy is a favoured tool of cell biologists in the study of intracellular relations using markers specifically bounded to organelles or using autofluorescence. During observation and multiple labelling, there exist problems of colour aberration that projects each emitted wavelength into a different spatial point. The dissertation will use image processing methods and information entropy with the identification of the focal level of each individual fluorophore´s response. The proposed methodology of fluorophores 3D mapping will utilize of the full information content of microscopy datasets.

Software sensors for monitoring of bioprocesses (assoc. Prof. Pavel Hrnčiřík)

Abstract: The quality of process control of biotechnological production processes used in the pharmacy and food industry is often constrained by the limited possibilities of on-line measurement of key process parameters (e.g. cell concentration, growth rate, production rate, etc.). One possible solution is the use of software sensors to continually estimate the values of key process indicators from on-line measurable process variables. The proposed work is focused on the study and application of the above methods for advanced monitoring of a selected biotechnological process.

Advanced Statistical Methods for Biomedical Data Analysis (assoc prof. Jan Mareš)

Abstract: Biomedical data analysis using advanced statistical methods is a very desired but non-trivial mathematical problem. Results can forward the research in the field and biomedicine to more precise and accurate diagnostics. The work assumes (i) the study of advanced statistical methods, (ii) the proposal of specific methods and algorithms for statistical analysis of selected biomedical data, and (iii) implementation and verification in the hospital.

Active protective surfaces based on organic composites for attenuation of radar radiation (assoc. Prof. Dušan Kopecký)

Abstract: Intensive use of radar detection technology in the field of industrial measurement, self-driving cars, civil aviation or surveillance or army systems increases the degree of autonomy of intelligent cyber-physics devices and improves the results of their decision-making as it provides irreplaceable and accurate information about the state and characteristics of the environment. Radar technology, however, is also an intense source of electromagnetic interference, which in its turn can affect or damage the sensitive electronic devices that the modern man is surrounded by. The work is devoted to the study of electromagnetic radiation attenuation in new types of nanostructured composites of conjugated systems of macromolecular substances and polymers. The aim is to develop thin low-density protective surfaces with the ability to efficiently absorb microwave radiation over a wide wavelength range, whose attenuation mode could be tuned by changing external conditions. Such surfaces can be used as active protection against electromagnetic interference.