prof. Ing. Valentine Provazník, Ph.D.

2. round (applications submitted from 01.07.2019 to 31.07.2019)

1. Advanced methods for cardiac arrhythmias classification

   The theme of the dissertation is aimed on design and development of new sophisticated methods for parametrization and classification of ECG records in order to timely diagnose cardiac arrhythmias. It will be mainly focused on the automatic detection of arrhythmias, which are poorly recognized by common ECG criteria and are often confused with other types of arrhythmias. Among such arrhythmias, they are atrial fibrillation and atrial flutter, which may have paroxysmal character and, consequently, may not be detected via existing methods. Multidimensional data analysis, time-frequency or nonlinear analysis are expected to be useful for addressing the topic. Automatic recognition of different types of cardiac arrhythmia implies the use of advanced machine learning methods, including state-of-the-art deep learning approaches yielding excellent results in image data classification. To develop and test the algorithms, publicly available data as well as data collected in frame of research projects at DBME will be used. The work will be a follow-up to the conducting research. PhD students will completed six-month internships at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.

   Tutor: Filipenská Marina, Ing., Ph.D.

2. Advanced methods for ECG signal quality estimation

   The topic of dissertation thesis is focused on continuous quality monitoring in long-term ECG records. The first part is to evaluate the quality of ECG signal recorded from different locations on the body using mobile recorder and possibilities of simultaneously recorded physical activity by gyroscope. The second part is the design of advanced algorithms for continuous and real-time estimation of the ECG quality and subsequent identification of the section of the same quality. Applicants are expected to programming skills in Matlab and base knowledge of the processing and analysis of 1D signal. PhD students will complete a six-month internships at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.

   Tutor: Smital Lukáš, Ing., Ph.D.

3. Advanced methods for the study of controlled cell motility and migration in regenerative medicine

   Cell motility and migration is a fundamental feature of a number of cell types involved in wound healing, hypoxic/necrotic regeneration, proximity and contact between dendritic and cancer cells, or between immunologically active cells and cancer cells. Current cell motility testing methods are limited to simplified microscopic tracking procedures in the transwell migration assay - long-term monitoring of cell motility in planar culture plastic. The dissertation will deal with research and development of new methods for studying motility and migration of cells using advanced microscope devices. The aim of this work is to create a methodology for the evaluation of cell migration in regenerative medicine in order to evaluate the efficiency and speed of regeneration. Part of the work will be the creation of a methodology for controlled simulation of chemotactic migration in a controlled environment. In the environment, levels or gradients of oxygen, carbon dioxide, and basic biochemical factors (glucose, lactate, pH, and more) will be provided. The environment may already contain pathological tissue or a pre-set tissue construct. Advanced methods of phase and fluorescence microscopy will be used to analyze the movement and properties of migrating cells. Microscopic methods will provide multiparametric and/or multimodal data, , the measurements will be conducted in a long time and in high detail. PhD students will complete a six-month internship at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.

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

4. Deep learning methods for processing of image sequences

   This topic deals with the application of deep artificial neural networks in the area of video processing and analysis. The primary focus will be on the detection, segmentation and tracking of people in video sequences with the focus on face segmentation. Two main applications will be considered - biometrics (e.g. person recognition, sex and age recognition) and biomedicine (e.g. heart rate or respiratory detection, facial expression recognition). It is expected that deeper study will be needed in the following areas: convolution neural networks, transfer learning for application in other tasks, progressive learning to solve new and complex problems and application of recurrent neural networks for segmentation and tracking objects in the image data. PhD students will complete a six-month internship at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.

   Tutor: Kolář Radim, doc. Ing., Ph.D.

5. Gait analysis in rehabilitation

   Gait analysis in rehabilitation is irreplaceable. In clinical practice applies a subjective rating walk to diagnose the severity of the disease or injury. This work will focus on the selection of appropriate parameters and analysis of data from a camera motion capture system that will be conducted in order to evaluate the effectiveness of selected rehabilitation process. The results will be applied to the evaluation of rehabilitation procedures of persons with mobility disabilities. PhD students will complete a six-month internship at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.

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

6. Genetic variation in cardiomyopathy and coronary artery disease

   Patients suffering cardiovascular diseases such as cardiomyopathy and coronary artery disease tend to cluster in families due to underlying monogenic or polygenic genetic architectures. The main aim of the project is search for genetic variation in these diseases in order to find causative genes and susceptibility loci. Distribution of the allele frequencies of the selected set of loci in a sample population will be analyzed and modelled. The study will be extended to identify loci that implicate pathways in blood vessel morphogenesis and inflammation related to the diseases. Data from 1000 Genomes Project and from CARDIoGRAMplusC4D Consortium project will be used to conduct large genome-wide bioinformatics analysis. There will opportunities to develop and apply research methodologies in statistical genetics and bioinformatics, develop skills in programming in high-level analysis packages, and develop skills in high-performance computing. PhD students will complete a six-month internship at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.

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

7. Medical image segmentation using deep learning techniques

   The theme of this thesis is aimed on medical image segmentation and classification using deep learning methods. The first aim of this thesis is to improve on actual methods for segmentation of 2D medical images. In next step these methods will be adapted for segmentation of 3D volume images, especially images from microCT system. The classification of images using deep learning methods will be also part of this thesis. Machine learning methods, especially neural networks, which represents new and perspective algorithms of image processing, will be used for the solution of this thesis. The main aim of this thesis is extend possibilities of automatic processing and classification of large volume of data like images from CT scanners. PhD students will complete a six-month internship at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.

   Tutor: Harabiš Vratislav, Ing., Ph.D.

8. New imaging approaches for retina diagnosis

   This topic focuses on analysis of retinal video sequences. It covers several areas - from data acquisition, including hardware modification of an experimental video-ophthalmoscope to processing and analysis of acquired video-sequences. The focus will be mainly on multispectral ophthalmoscopy, which is a promising method for obtaining diagnostically valuable information, in addition to video-ophthalmoscopy. During this project, it is expected to modify the existing video-ophthalmoscope to a multispectral system, eventually another extension (e.g. adaptive optics). The processing of the measured sequences will then be focused on segmentation of vascular tree, evaluation of vascular pulsation and retinal tissue perfusion or pulse oximetry using multispectral sequences. PhD students will complete a six-month internship at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.

   Tutor: Kolář Radim, doc. Ing., Ph.D.

9. New methods of rational drug design for finding novel HDAC inhibitors as anticancer agents

   Carcinogenesis cannot be explained only by genetic alterations, but also involves epigenetic processes (DNA methylation, histone modifications and non-coding RNA deregulation). Modification of histones by acetylation plays a key role in epigenetic regulation of gene expression and is controlled by the balance between histone deacetylases (HDAC) and histone acetyltransferases (HAT). HDAC inhibitors induce cancer cell cycle arrest, differentiation and cell death, reduce angiogenesis and modulate immune response. HDAC inhibitors seem to be promising anti-cancer drugs particularly in the combination with other anti-cancer drugs and/or radiotherapy. The objective of the current study is to establish structure activity relationships using virtual screening, docking, energetic based pharmacophore modelling, atom based 3D QSAR models and their validation. The outcome of these studies could be further employed for the design of novel HDAC inhibitors for anticancer activity. PhD students will complete a six-month internship at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.

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

10. 4D bioprinting based on the maturation of engineered tissue constructs

    The work is focused on the research of new approaches in 3D bioprinting based on the external stimulation or on the maturation of engineered tissue construct. The aim is to create a tissue construct in the form of cell-coated scaffolds useful as a vascular replacement or as a means of regenerating damaged heart tissue. As external stimulus, magnetic field, temperature gradient and pH change will be used. The proposed procedure will replace the need for post-printing procedures. The initial variant will be based on the use of a suspension of human HUVEC endothelial cells and human mesenchymal stem cells. The project requires mastery of cell experimentation, extrusion 3D bioprinting and fluorescence confocal microscopy imaging. PhD students will complete a six-month internship at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.

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

1. round (applications submitted from 01.04.2019 to 15.05.2019)

1. Advanced algorithms for monitoring human activity using mobile sensors

   The theme of this dissertation is aimed on monitoring and evaluation of activities performed by individuals using sensors commonly available in mobile devices (accelerometer, GPS, microphone, heartbeat sensor) and it can be divided into two parts. The goal of the first part is to analyze possibilities of mobile devices available on consumer market, become familiar with the types of sensor data and assess their potential. The goal of the second part is to design advanced algorithms for processing of captured data to identify different types of performed activities (sitting, standing, walk, run, fall). Applicants are expected to be familiar with Matlab programming and have an overview in the area of processing and analysis of one-dimensional digital signals. PhD students will completed six-month internships at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.

   Tutor: Vítek Martin, Ing., Ph.D.

2. Advanced methods for genome annotation and functional description of non-model organisms in biotechnology research

   The thesis will deal with development of novel methodology for genome annotation and functional description of organisms by utilizing genome and transcriptome sequencing data. The aim of the thesis is to establish method for a refinement of open reading frames (ORF) identification in a genome sequence by utilizing RNA-Seq data and for functional annotation with gene ontology (GO). Based on this annotation refinement and in a combination with additional methods for phenotype description (liquid chromatography, flow cytometry, microscopy, etc.) under various conditions, the methods will be supplemented for inference of mutual regulatory relationships among particular genome elements in non-model organisms. Their annotation is currently insufficient for high quality biotechnology research. Therefore, the proposed methods will be applied on the description of solventogenic bacteria from the genus Clostridium, promising biofuels producers, whose broader utilization in industry is complicated by this insufficient functional description caused by lack of tools for analyses of non-model organisms. General knowledge of an applicant in bioinformatics, especially sequencing data processing, and in systems biology, including graph theory, is expected. PhD students will complete a six-month internship at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.

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

3. Analysis of movement stereotypes in sports performance

   Motion analysis in sports is irreplaceable. A detailed analysis of movement stereotypes leads to improved quality of training plans and improve sports results of training individuals. Analysis can also be used for diagnostic purposes - monitoring faulty movement patterns after injuries in order to clarify procedures for rehabilitation treatments. This work will be focused on monitoring specific movement stereotypes, selection of appropriate parameters and subsequent analysis of data, which will be performed in order to describe the motion stereotypes in sports performance. The study will be carried out in cooperation with the Centre of Sports Activities of BUT. PhD students will complete a six-month internship at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or a part-time contract beyond the state stipend when joining a grant project or engaging in teaching.

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