The doctoral study provides the graduates of MSc study in the area of biomedical electronics and biocybernetics with a higher degree of education, deepening their theoretical background.
The study is aimed at deepening of theoretical knowledge of students in advanced mathematics, physics and in disciplins forming the theoretical basis of the chosen field. Also, necessary experience in experimental work and in processing of the obtained results should be provided, including exploitation of advanced methods of applied informatics.
The final goal is that the students will master methods of scientific research.

A graduate of the doctoral study is expected to be a distinct personality with a recognised research result, wide horizon of knowledge and ability to solve complex scientific and technical-research tasks in the field of biomedical electronics and biocybernetics and in neighbouring fields.
Maximum flexibility and professional adaptivity is the undisputed property of a graduate of doctoral study.
The graduates of the doctoral study in biomedical electronics and biocybernetics will be capable of working as scientists and researchers involved in basic or applied research namely in medical or biological area, as leading specialists in development and construction departments of research and development institutions, and in manufacturing enterprises or institutions exploiting advanced technology, namely in biomedical field.

Graduate of doctoral programme should be a strong personality with substantial scientific results, large horizon and ability to solve complex scientific and research technical tasks in area of biomedical electronics and biocybernetics. He/she will have maximum flexibility and professional adaptability in wide area of biomedical engineering. Graduates will be able to work as scientific and research staff in basic and applied research, as specialists in development, construction and production, in research institutes and at industrial companies and users of medical devices and applied information technologies in medicine and biology.

prof. Ing. Jiří Jan, CSc.

1. Artificial Intelligence in Processing of Genomic and Proteomic Data

   The project is focused on development of methods and algorithms for processing of genomic and proteomic data with the use of artificial intelligence. The methods will be based on modern tools for decision making, pattern recognition, clustering and modelling by artificial neural networks. The methods will be used in applications of searching subsequences including mutations in extremely large sequences. The methods will be verified on user data from DNA sequenation and from public genomic and proteomic databases.

   Tutor: Provazník Valentine, prof. Ing., Ph.D.

2. Electrophysiology of isolated heart in experimental cardiology.

   The project is focused on analysis of biosignals recorded simultaneously from isolated animal heart during experiments. The changes of calcium concentrations, action potentials and electrograms will be studied. Based on biosignal analysis, the pattern recognition methods will be applied for classification of heart cycles during global ischemia.

   Tutor: Kolářová Jana, doc. Ing., Ph.D.

3. Modeling and Analysis of Signals in Perfusion Imaging

   The project is focused on investigation of new methods of perfusion imaging in medical diagnostics. These are methods for estimation of diagnostically significant parameters of tissue perfusion, based on dynamic tissue imaging (using e.g. MRI, CT, PET, ultrasonography) after application of contrast agent. The project will include design of new data acquisition procedures (focused on ultrasonography), models of contrast agent kinetics, algorithms for signal processing with the goal of robust perfusion-parameters estimation and testing on synthetic and real data. The work will be partly supported by a running grant GAČR.

   Tutor: Jiřík Radovan, doc. Ing., Ph.D.

4. Multimodal analysis of ophthalmological image data

   The subject of the project is the analysis of ophthalmological image data, particularly with the aim of comparison of diagnostic information provided by the individual imaging modalities and of investigating the possibilities of higher utilisation of this information based on image data moltimodal fusion. The project may be supported by the national research centre Data, Algorithms and Decission making.

   Tutor: Jan Jiří, prof. Ing., CSc.