Full-time study

4 years

prof. Ing. Valentine Provazník, Ph.D.

Chairman :
prof. Ing. Valentine Provazník, Ph.D.
Councillor internal :
doc. Ing. Radim Kolář, Ph.D.
doc. Ing. Jana Kolářová, Ph.D.
doc. Ing. Daniel Schwarz, Ph.D.
Councillor external :
Prof. José Millet Roig
prof. Mgr. Jiří Damborský, Dr.
prof. MUDr. Marie Nováková, Ph.D.
prof. Ewaryst Tkacz, Ph.D.,D.Sc.
prof. Pharm.Dr. Petr Babula, Ph.D.
prof. Dr. Marcin Grzegorzek

The doctoral studies of a student follow the Individual Study Plan (ISP), which is defined by the supervisor and the student at the beginning of the study period. The ISP is obligatory for the student, and specifies all duties being consistent with the Study and Examination Rules of BUT, which the student must successfully fulfill by the end of the study period. The duties are distributed throughout the whole study period, scored by credits/points and checked in defined dates. The current point evaluation of all activities of the student is summarized in the “Total point rating of doctoral student” document and is part of the ISP. At the beginning of the next study year the supervisor highlights eventual changes in ISP. By October, 15 of each study year the student submits the printed and signed ISP to Science Department of the faculty to check and archive.
Within mainly the first four semesters the student passes the exams of compulsory, optional-specialized and/or optional-general courses to fulfill the score limit in Study area, and concurrently the student significantly deals with the study and analysis of the knowledge specific for the field defined by the dissertation thesis theme and also continuously deals with publishing these observations and own results. In the follow-up semesters the student focuses already more to the research and development that is linked to the dissertation thesis topic and to publishing the reached results and compilation of the dissertation thesis.
By the end of the second year of studies the student passes the Doctor State Exam, where the student proves the wide overview and deep knowledge in the field linked to the dissertation thesis topic. The student must apply for this exam by April, 30 in the second year of studies. Before the Doctor State Exam the student must successfully pass the exam from English language course.
In the third and fourth year of studies the student deals with the required research activities, publishes the reached results and compiles the dissertation thesis. As part of the study duties is also completing a study period at an abroad institution or participation on an international research project with results being published or presented in abroad or another form of direct participation of the student on an international cooperation activity, which must be proved by the date of submitting the dissertation thesis.
By the end of the winter term in the fourth year of study the full-time students submit the elaborated dissertation thesis to the supervisor, who scores this elaborate. The combined students submit the elaborated dissertation thesis by the end of winter term in the fifth year of study. The final dissertation thesis is expected to be submitted by the student by the end of the fourth or fifth year of the full-time or combined study form, respectively.
In full-time study form, during the study period the student is obliged to pass a pedagogical practice, i.e. participate in the education process. The participation of the student in the pedagogical activities is part of his/her research preparations. By the pedagogical practice the student gains experience in passing the knowledge and improves the presentation skills. The pedagogical practice load (exercises, laboratories, project supervision etc.) of the student is specified by the head of the department based on the agreement with the student’s supervisor. The duty of pedagogical practice does not apply to students-payers and combined study program students. The involvement of the student in the education process within the pedagogical practice is confirmed by the supervisor in the Information System of the university.

3. round (applications submitted from 01.12.2024 to 15.12.2024)

1. AI-Driven Human Exome Analysis in Clinical Data

   Exome analysis has become a cornerstone of clinical genomics, enabling the identification of rare and common genetic variants linked to diseases. Despite advances in sequencing technologies, the challenge lies in integrating computational methodologies to interpret exome data with precision. This includes leveraging heuristic algorithms and artificial intelligence (AI) to analyze data efficiently and improve variant annotation. One promising application is the calculation of the PSI (Percent Spliced-In) coefficient, critical for understanding alternative splicing in disease-related genes. This work focuses on developing an AI-based pipeline for analyzing human exomes in clinical datasets. The research will involve the design of heuristic algorithms optimized for calculating PSI coefficients, which quantify alternative splicing patterns in genes of clinical interest. The project's main objectives are: 1. To develop and validate a heuristic-algorithm-based method for PSI computation. 2. To integrate AI for enhanced variant interpretation, focusing on alternative splicing. 3. To identify clinically actionable splicing variants linked to complex diseases. 4. To deploy the pipeline within clinical genomics settings, enabling personalized therapeutic strategies. The project will be solved mainly at the Department of Biomedical Engineering. However, cooperation with our national partner University Hospital Ostrava 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.

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

2. Bioreactor optimization for cultivation of thermophiles

   White biotechnology, i.e. a technology that uses living cells to produce value added chemicals, usually loses the competition with standard petrochemical production due to higher financial costs. The reason can be found in the need to protect these processes against contamination. This inefficiency could be reduced by using naturally robust organisms, so called extremophiles. However, these organisms are not so well studied, partly also because of the lack of instrumentation for extremophilic cultivation on a small scale in laboratory bioreactors. The topic is focused on developing a small laboratory bioreactor especially suited for thermophilic cultivations. Large industrial processes usually generate waste heat that is unfavourable for mesophiles and needs to be reduced for them to proliferate. On the other hand, this environment is naturally suitable for extremophiles, particularly thermophiles. Unlike large scale processes, small scale lab cultivation does not produce waste heat, therefore, the heat has to be added for successful cultivation and research of thermophiles. Such experiments are needed to develop novel concepts as the Next-Generation Industrial Biotechnology concept that relies on the use of naturally robust organisms. Unfortunately, small bioreactors designed for thermophilic cultivations are currently missing. The aim of the research is to develop novel hardware for cultivations of bacterial thermophiles and its software control for various cultivation modes. A wide range of currently available parts will be used rather than building the reactor up from scratch. Platforms like Chi.Bio can be used as a base for it presents an open system orchestrated through Arduino and programmable in Python. Thus, it offers almost unlimited possibilities for bioreactor augmentation. The project will be solved mainly at the Department of Biomedical Engineering. However, cooperation with our national (University Hospital Brno, the Faculty of Chemistry BUT, and Czech Collection of Microorganisms) and foreign partners (Ludwig-Maximilians-Universität München in Germany and HES-SO Valais-Wallis in Switzerland) 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: Sedlář Karel, doc. Mgr. Ing., Ph.D.

3. Computational Polygenic Risk Score Models for Sudden Cardiac Arrest in Central European Populations

   Sudden cardiac arrest (SCA) is a leading cause of mortality, with a complex interplay of genetic and environmental factors contributing to its risk. Polygenic Risk Scores (PRS) are emerging as vital tools for assessing genetic susceptibility to SCA. However, existing PRS models often fail to account for the unique genetic makeup of geographically and ethnically homogeneous populations, such as the Central European population. This work aims to design and validate a PRS model tailored to the Central European population, utilizing large-scale genomic datasets from collaboration with University Hospital Ostrava. The research will integrate genomic data with AI-based statistical modeling techniques to identify genetic variants most predictive of SCA. Key objectives include: 1. Development of a computational pipeline for PRS calculation incorporating population-specific allele frequencies. 2. Application of machine learning techniques to optimize variant weighting within the PRS framework. 3. Validation of the PRS model on Central European cohorts to ensure predictive accuracy. 4. Exploration of gene-environment interactions and their influence on SCA risk. The project will be solved mainly at the Department of Biomedical Engineering. However, cooperation with our national partner University Hospital Ostrava 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.

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

4. Modern image processing methods in cardiac MRI applications

   Nuclear magnetic resonance imaging is one of the most advanced imaging systems in medicine. The development of these methods and the improved availability of these systems brings additional areas in which these methods can be used for diagnosis. This brings with it much larger volumes of data acquired by this modality and the resulting need for new methods that will allow for the processing of these data while providing more advanced and accurate diagnostics. One of these areas is cardiac MRI, which is the topic of this dissertation. The very first step is the correct orientation of the heart, i.e. finding the radiological planes that are important for the correct imaging of the heart using nuclear magnetic resonance. Here it is shown that the use of machine learning based methods (deep learning) could enable automatic detection from the survey data and thus can both speed up the scanning process and make it more accurate. The next step is to design appropriate methods to support the diagnosis of heart disease. These include both segmentation methods that can lead to a more detailed analysis of the heart (cardiac volumes, myocardial thickness, etc.) and other advanced methods based on deep learning to support diagnosis (detection of tissue changes, lesions, anatomical differences, etc.). However, cooperation with external partners - national clinical centres (FN Brno, VFN Prague, FNUSA/ICRC Brno) and foreign institutions (IRST IRCCS Meldola Italy, Philips Healthcare Netherlands, DKFZ Heidelberg Germany) is envisaged, enabling clinical evaluation of results and their discussion with expert physicians. 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.

5. New approaches for multimodal retinal image processing and analysis

   This topic is focuses on advancing ophthalmology through the development of novel image processing and analysis methods for multimodal retinal imaging. By leveraging state-of-the-art techniques such as adaptive optics, spectral imaging, and machine learning, the study aims to enhance the detection and diagnosis of specific eye diseases. The work also explores the integration of multimodal imaging data to provide a holistic view for clinical decision-making, thereby improving diagnostic accuracy, treatment planning, and monitoring of disease progression. The dissertation topic based on collaboration with Lappeenranta University of Technology and the PhD student will be under double supervision during the PhD studies.

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

6. New approaches in computational analyses of bacterial communities for biotechnology

   Thanks to their diversity, non-model bacteria represent an inexhaustible resource for microbial biotechnology. While tools, including the computational ones, to study pure bacterial cultures are developed to at least a certain point, their counterparts for analysis of mixed cultures are underdeveloped or completely missing. This prevent us to further study biotechnological capacity of bacterial consortia to produce value added chemicals. The topic is focused on computational methods for a comprehensive analysis of microbial consortia in order to reveal their functional capacity for industrial biotechnology and production of value added chemicals, primarily bioplastics. While particular tools for taxonomic profiling based on amplicon sequencing and metagenome analysis based on shotgun sequencing exist, they are oriented to perform descriptive rather than functional analysis. This provides only limited use for biotechnology research where the emphasis is put on function. This is partly caused also by the lack of tools oriented on processing of bacterial metatranscriptomes. Finally, there is an absolute lack of tools to connect potential functional capacity inferred from a metagenome with running biological processes measured with metatranscriptomics and metabonomics approaches. The aim of the research is to set up comprehensive computational pipeline to analyse diversity of a selected mixed bacterial culture, to set up a metagenome of this community, and to match its observed behaviour through analyses of other omics data revealing running biological and metabolic processes. The pipeline will include specific steps to process short NGS as well as long TGS reads to cover all currently used sequencing technologies. The project will be solved mainly at the Department of Biomedical Engineering. However, cooperation with our national (University Hospital Brno, the Faculty of Chemistry BUT, and Czech Collection of Microorganisms) and foreign partners (Ludwig-Maximilians-Universität München in Germany and HES-SO Valais-Wallis in Switzerland) 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: Sedlář Karel, doc. Mgr. Ing., Ph.D.

7. New approaches in recruiting bacterial genomes from metagenomes

   Recent advances in DNA sequencing allowed routine sequencing of environmental samples. However, current computational tools hardly keep up with constantly changing lab techniques and the growing output of sequencing devices. Therefore, novel computationally efficient techniques are needed to recruit particular genomes from metagenomes. The topic is focused on methods for recruiting particular bacterial genomes from environmental samples, i.e., metagenomes. While in the past all newly described bacteria had to be isolated and their culture had to be made publicly available, a recent initiative SeqCode brought a nomenclatural code for prokaryotes described directly from sequence data as many microbial species are uncultivable with current techniques. Moreover, even for newly published cultured bacteria, environmental evidence based on searching in publicly available metagenomes is nowadays required by scientific journals. Although tools to produce metagenome-assembled genomes exist, searching metagenomes for particular analysed genomes is done exclusively with BLAST and is not rigorously described. Unfortunately, due to the repetitive segments of bacterial genomes, false hits are always found and quantification of data, i.e., assuming an abundance of a genome in a metagenome, is therefore biased. The aim of the research is to find a method for quantification as precise as possible. The applied method will include specific steps to process short NGS as well as long TGS reads to cover all currently used sequencing technologies. The project will be solved mainly at the Department of Biomedical Engineering. However, cooperation with our national (University Hospital Brno, the Faculty of Chemistry BUT, and Czech Collection of Microorganisms) and foreign partners (Ludwig-Maximilians-Universität München in Germany and HES-SO Valais-Wallis in Switzerland) 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. 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: Sedlář Karel, doc. Mgr. Ing., Ph.D.

8. 3D Bio Printing of Cancer-Model Structures with Controlled Polymerization Using PET-RAFT Technique and Variable Light Intensity for Drug Testing Applications

   This dissertation thesis focuses on the innovative application of 3D bioprinting technology for creating cancer-model structures with precise control over polymerization using the PET-RAFT technique and variable light intensity. The research aims to develop a sophisticated platform for simulating cancer tissues in a controlled in vitro environment, allowing for the testing of various medications and treatment modalities. By leveraging advanced biofabrication techniques and tailored polymerization processes, this study contributes to the advancement of personalized medicine and drug efficacy assessment in oncology research. Responsibilities include research, experimental design, data analysis, collaboration, publication, innovation, regulatory compliance, and continuous professional development in the field of 3D bioprinting for cancer modeling and drug testing applications. As part of their studies, doctoral students complete six-month internships at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or part-time in addition to the state stipend when participating in a grant project or participating in teaching.

   Tutor: Fohlerová Zdenka, doc. Mgr., Ph.D.

2. round (applications submitted from 01.07.2024 to 31.07.2024)

1. Advanced image processing approaches in adaptive optics retinal imaging

   Over the past decade, significant advancements in retinal imaging, particularly through adaptive optics (AO), have revolutionized the ability to achieve cellular-level resolution. This breakthrough allows for in-vivo analyses of previously unexplored retinal structures, necessitating the development of a novel and robust image analysis pipeline. This PhD project primarily focuses on the analysis of retinal vascularity, encompassing segmentation, pathology detection, multimodal image registration, and image quality assessment. The main tasks in this project include development of an innovative analysis pipeline mainly for AO retinal images with vascularities (wall/lumen segmentation, retinal narrowing detection, morphology analysis), design of new diagnostic markers and statistical analysis of correlation across the retinal image data, acquired by various imaging devices. While the project is primarily based at the Department of Biomedical Engineering, collaboration with international partners, namely Leipzig University and the University of Minnesota, USA, is anticipated.

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

2. Advanced methods for MRI image analysis to improve image clarity and disease diagnosis

   Magnetic resonance imaging is nowadays becoming an increasingly accessible and progressive modality, often replacing previous diagnostic standards, and often becoming the first-choice examination. Consequently, the amount of data acquired by this modality is also increasing and thus the time requirements for its analysis by medical experts are higher. Supporting diagnostic tools then provide medical experts with an easier and more accurate view of the captured data, making it easier to work with it and offering the possibility of automated supporting diagnostics. Specifically, this can include the co-registration of contrast scans at different stages, automated segmentation of areas or pathologies, and their analysis in relation to the current diagnosis or prognosis. The topic focuses on the development, implementation and validation of advanced image processing techniques involving deep learning methods. The student will be work with data from MR modality, such as MRI of breast or brain tumors (gliomas), where the main task is to provide data pre-processing, extraction of parametric maps from multiphase or perfusion scans, analysis of the resulting parameters, and correct interpretation of the resulting relationships to the current diagnosis or prognosis. At the initial stage, however, this requires a thorough study of the issues, research and familiarization with the data and their pre-processing. As part of their studies, doctoral students complete several month-long internships at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or part-time in addition to the state stipend when participating in a grant project or participating in teaching.

   Tutor: Jakubíček Roman, Ing., Ph.D.

3. Advanced methods of medical image analysis in modern CT scanners

   The topic will aim to development of advanced image processing and analysis methods involving machine learning and deep learning approaches with a scope for multiparametric images acquired by multilayer CT detectors. The student will focus on the development, implementation and validation of preprocessing, segmentation, detection, classification, and prediction tasks considering the character of multiparametric images. The proposed complex computer-aided diagnostic tool will help increase diagnostic accuracy and reproducibility, speed of the examinations and decrease the inter-/intra-expert variability and routine workload. The topic will be solved at the Department of Biomedical Engineering. However, cooperation with our external partners is expected – national clinical institutions (FN Brno, VFN Prague, FNUSA/ICRC Brno) and foreign institutions (IRST IRCCS Meldola Italy, Philips Healthcare Netherlands, DKFZ Heidelberg Germany), allowing clinical evaluation of the results and their discussion with medical experts. As part of their studies, doctoral students complete several month-long internships at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or part-time in addition to the state stipend when participating in a grant project or participating in teaching.

   Tutor: Chmelík Jiří, Ing., Ph.D.

4. Bioreactor optimization for cultivation of thermophiles

   White biotechnology, i.e. a technology that uses living cells to produce value added chemicals, usually loses the competition with standard petrochemical production due to higher financial costs. The reason can be found in the need to protect these processes against contamination. This inefficiency could be reduced by using naturally robust organisms, so called extremophiles. However, these organisms are not so well studied, partly also because of the lack of instrumentation for extremophilic cultivation on a small scale in laboratory bioreactors. The topic is focused on developing a small laboratory bioreactor especially suited for thermophilic cultivations. Large industrial processes usually generate waste heat that is unfavourable for mesophiles and needs to be reduced for them to proliferate. On the other hand, this environment is naturally suitable for extremophiles, particularly thermophiles. Unlike large scale processes, small scale lab cultivation does not produce waste heat, therefore, the heat has to be added for successful cultivation and research of thermophiles. Such experiments are needed to develop novel concepts as the Next-Generation Industrial Biotechnology concept that relies on the use of naturally robust organisms. Unfortunately, small bioreactors designed for thermophilic cultivations are currently missing. The aim of the research is to develop novel hardware for cultivations of bacterial thermophiles and its software control for various cultivation modes. A wide range of currently available parts will be used rather than building the reactor up from scratch. Platforms like Chi.Bio can be used as a base for it presents an open system orchestrated through Arduino and programmable in Python. Thus, it offers almost unlimited possibilities for bioreactor augmentation. The project will be solved mainly at the Department of Biomedical Engineering. However, cooperation with our national (University Hospital Brno, the Faculty of Chemistry BUT, and Czech Collection of Microorganisms) and foreign partners (Ludwig-Maximilians-Universität München in Germany and HES-SO Valais-Wallis in Switzerland) 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: Sedlář Karel, doc. Mgr. Ing., Ph.D.

5. Development and Evaluation of a 3D Bioprinted Body-on-a-Chip System for Therapeutic Modalities and Drug Efficacy Assessment

   The dissertation thesis titled „Development and Evaluation of a 3D Bioprinted Body-on-a-Chip Systém for Drug Efficacy and Comparative Analysis of Therapeutic Modalities“ explores the development and validation of a novel 3D bioprinted body-on-a-chip platform for assessing drug efficacy and comparing different therapeutic modalities. The study aims to advance the field of pharmacological screening by providing a versatile and accurate model for testing the effectiveness of various treatment methods. Through comprehensive analysis and validation, this research contributes to the understanding of personalized medicine and precision healthcare interventions. Responsibilities include research, experimental design, data analysis, collaboration, publication, innovation, regulatory compliance, and continuous professional development in the field of 3D bioprinting for cancer modeling and drug testing applications. As part of their studies, doctoral students complete several month-long internships at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or part-time in addition to the state stipend when participating in a grant project or participating in teaching.

   Tutor: Fohlerová Zdenka, doc. Mgr., Ph.D.

6. Exploring Host-Microbiome Interaction Dynamics through Advanced Bioinformatics Analysis

   The PhD study will focus on utilizing advanced bioinformatics methods to unravel the complexities of host-microbiome interactions. Through a multidisciplinary approach that integrates genomics, metagenomics, metatranscriptomics, and phenotype screening, this research aims to dissect the underlying mechanisms governing the interplay between the host and the microbiome. The overarching goal is to deepen our understanding of the genetic factors shaping microbial communities across diverse host environments and their implications for health and disease. Additionally, the study aims to uncover the fundamental mechanisms driving antibiotic resistance and identify novel therapeutic targets, thereby paving the way for innovative strategies to combat antibiotic resistance, including the potential application of probiotics in both humans and animals. Our bioinformatic approaches will encompass the analysis of diverse sequencing data types derived from viral and bacterial pathogens, probiotic strains, and their host. This includes identifying novel probiotic strains, characterizing their metabolic capacity, and exploring the evolution of bacterial genomes across different organs, time points, and animal hosts. Furthermore, the study will investigate the co-evolution dynamics within the host environment. PhD students will have the opportunity to complete a three-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: Čejková Darina, Mgr. Bc., Ph.D.

7. New approaches in computational analyses of bacterial communities for biotechnology

   Thanks to their diversity, non-model bacteria represent an inexhaustible resource for microbial biotechnology. While tools, including the computational ones, to study pure bacterial cultures are developed to at least a certain point, their counterparts for analysis of mixed cultures are underdeveloped or completely missing. This prevent us to further study biotechnological capacity of bacterial consortia to produce value added chemicals. The topic is focused on computational methods for a comprehensive analysis of microbial consortia in order to reveal their functional capacity for industrial biotechnology and production of value added chemicals, primarily bioplastics. While particular tools for taxonomic profiling based on amplicon sequencing and metagenome analysis based on shotgun sequencing exist, they are oriented to perform descriptive rather than functional analysis. This provides only limited use for biotechnology research where the emphasis is put on function. This is partly caused also by the lack of tools oriented on processing of bacterial metatranscriptomes. Finally, there is an absolute lack of tools to connect potential functional capacity inferred from a metagenome with running biological processes measured with metatranscriptomics and metabonomics approaches. The aim of the research is to set up comprehensive computational pipeline to analyse diversity of a selected mixed bacterial culture, to set up a metagenome of this community, and to match its observed behaviour through analyses of other omics data revealing running biological and metabolic processes. The pipeline will include specific steps to process short NGS as well as long TGS reads to cover all currently used sequencing technologies. The project will be solved mainly at the Department of Biomedical Engineering. However, cooperation with our national (University Hospital Brno, the Faculty of Chemistry BUT, and Czech Collection of Microorganisms) and foreign partners (Ludwig-Maximilians-Universität München in Germany and HES-SO Valais-Wallis in Switzerland) 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: Sedlář Karel, doc. Mgr. Ing., Ph.D.

8. New imaging and image processing approaches in ophthalmology

   Over the past decade, retinal imaging has advanced significantly, encompassing both anatomical and functional aspects such as flow, perfusion, blood velocity, and tissue oxygenation. These methods are crucial for diagnosing retinal and systemic diseases. This project focuses on developing an ophthalmic device and image processing techniques to evaluate retinal oxygenation and blood circulation. A basic setup of video-ophthalmoscope was designed and validated over three years. It can capture retinal video sequences at specific wavelengths and acquire various biosignals like electrocardiogram, photoplethysmographic, and respiratory signals. This project will contribute to interdisciplinary research covering retinal imaging, functional assessment, advanced image processing, and machine learning. The goal is to establish a methodology for evaluating retinal oxygenation and identifying potential biomarkers for disease diagnosis. Your main tasks will include analysis of retinal video-sequences with the aim to extract specific parametric feature maps related to blood vessel pulsation, photoplethysmographic blood volume assessment and oxygen saturation estimation. Opto-mechanical modification of video-ophthalmoscope for spectral retinal imaging and development of analysis pipeline for multimodal retinal images processing (image segmentation, classification etc.). Project will be solved mainly at the Department of Biomedical Engineering. However, cooperation with our foreign partners is expected - Leipzig University in Germany and University of Minnesota, USA. As part of their studies, doctoral students complete several month-long internships at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or part-time in addition to the state stipend when participating in a grant project or participating in teaching. As part of their studies, doctoral students complete several month-long internships at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or part-time in addition to the state stipend when participating in a grant project or participating in teaching.

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

9. New methods for studying skin layers in drug application and tissue regeneration

   Examination and accurate qualification of skin and subcutaneous layers during their regeneration is a very topical biomedical problem. This problem is also related to the qualification of tissue properties at different depths for the analysis of stability or degradation of transplants and implants in regenerative medicine. The research topic focuses on the development and testing of a methodology for trans endodermal delivery of different types of drugs (labelled nanoparticles, liposomes, exosomes or other particles) through model and real skin layers. The Ph.D. student will primarily conduct research in the biology laboratory and will focus on the establishment of model skin epithelial cultures and the application of laboratory procedures, trans-epithelial/endothelial electrical resistivity methods, and confocal fluorescence microscopy techniques to test the model layer and analyze drug transfer across the model layer in in-vivo experiments. It will also involve the use of assistive techniques (e.g. optical coherence tomography) to test transfers to real skin in in-vivo experiments in animal models. The PhD student will be involved in interdisciplinary research in a project that involves working with endothelial and epithelial cells, creating cell monolayers and multilayers including model layer testing, testing and application of advanced drugs, and using advanced instrumentation and methodologies to acquire and interpret imaging data and further analyze it. The topic is provided in collaboration with the Research Facility of the The Veterinary Research Institute (VRI). As part of their studies, doctoral students complete several month-long internships at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or part-time in addition to the state stipend when participating in a grant project or participating in teaching.

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

10. Utilization of signal processing techniques for refinement of nanopore sequencing data decoding

    The aim of the dissertation is to develop methodology for pre-processing of raw nanopore sequencing data consisting from signal reads called “squiggles”. The proposed procedure should precede DNA sequence decoding, where the neural networks are used exclusively nowadays. The decoding step called “basecalling” is the main source of errors in nanopore sequencing data processing. Although the nowadays basecalling methods for nanopore sequencing have significantly increased accuracy in the last years, it can fall to 95 % and that is insufficient for clinical utilization. Appropriate combination of advance signal filtering of high level noise, signal segmentation into specific sections called “events” corresponding to DNA symbols and mutual adjustment of events durations by dynamic time warping can significantly improve accuracy of genetic information decoding. The applicant is expected being mastering basic methodology of processing and analysis of genomic data and should also have an overview in the field of processing and analysis of 1D signals. The programming in appropriate environment is commonplace. The topic will be solved in cooperation with the Children's Hospital - University Hospital Brno. 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: Vítková Helena, Ing., Ph.D.

1. round (applications submitted from 01.04.2024 to 30.04.2024)

1. Computational detection of small RNAs in bacterial genomes

   Thanks to their diversity, non-model bacteria represent an inexhaustible resource for microbial biotechnology. Their utilization is only limited by our lack of knowledge regarding the regulation of processes they are capable to perform. The particular problem lies in non-coding regulators, mainly small RNAs (sRNAs), that are not so widely studied as coding genes. During the last years, sRNAs were shown to play important regulatory roles in diverse cellular processes by participating in post-transcriptional regulation of gene expression. This is the reason why sRNAs are drawing more attention than ever before. The topic is focused on methods for computational inference of sRNA genes from bulk RNA-Seq datasets. While a plethora of specialized techniques for sRNA experimental identification exists, e.g., GRIL-Seq, RIP-Seq, RIL-Seq, their use in non-model bacteria is limited for their technical complexity. On the other hand, even standard RNA-Seq contains information on non-coding elements, including sRNAs, that can be mined by a computational approach. Unfortunately, current computational tools for sRNA inference does not match current standards in data processing. They require definition of threshold for detection that is dependent on sequencing depth and errors. Thus, they are not widely applicable for various sequencing platforms and libraries. The aim of the research is to find a method for sRNA inference without setting any additional parameters. Instead, the method will build upon thorough analysis of input dataset in order to make the detection independent of a sequencing library and platform. The applied method will include specific steps to process short NGS as well as long TGS reads to cover all currently used sequencing technologies. The project will be solved mainly at the Department of Biomedical Engineering. However, cooperation with our national (University Hospital Brno, the Faculty of Chemistry BUT, and Czech Collection of Microorganisms) and foreign partners (Ludwig-Maximilians-Universität München in Germany and HES-SO Valais-Wallis in Switzerland) 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: Sedlář Karel, doc. Mgr. Ing., Ph.D.

2. Detection and characterization of pulmonary nodules in lung cancer low-dose CT screening

   The topic is focused on methods for detection and characterization of pulmonary nodules in lung cancer low-dose CT screening image datasets. All data are available at cooperating institution Masaryk Memorial Cancer Institute in Brno where the screening programme is running since September 2022. The basic task for the topic is detection of nodules in lung cancer with various techniques of image processing. This part is well described in literature and several studies are published each year. Nodules are in form of opacities in lung parenchyma with no relation to a normal anatomy. Second task is nodule characterization based on classification on two main criteria – size and type. The aim of characterization is to find predictors of tumours malignancy. The results will be compared with an expert in radiology field and also with commercially available CAD system for CT scans evaluation. As part of their studies, doctoral students complete several month-long internships at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or part-time in addition to the state stipend when participating in a grant project or participating in teaching.

   Tutor: Mézl Martin, Ing., Ph.D.

3. Electroconductive biohybrid hydrogel for tissue engineering

   The dissertation thesis will integrate the emerging field of conductive hydrogels, optics, and computational models to study cardiomyocyte function in vitro. Patterned conductive hydrogels and electrical stimulation will be used to prepare cardiac tissue constructs with defined geometry. Optical recording of electrophysiological parameters and cellular forces generated on gels with range of conductivity will drive computational models of signal propagation and remodeling of contractile apparatus. Finally, regenerative application of Janus hydrogel, to bridge conductive blockades in vitro, will be tested. The conductive hydrogels will be prepared from natural and synthetic polymers with conducting PEDOT:PSS. The project involves preparation of hydrogels with desired properties, physico-chemical characterization, patterning, and applications of in vitro hydrogel platforms, including signal dynamics and mechanosensing. In the collaboration with the group of Mechanobiology of disease from FNUSA. From these points, we are looking for a motivated, enthusiastic student who is not afraid of an interdisciplinary topic and cooperation with top institutes in Brno. As part of their studies, doctoral students complete six-month internships at attractive partner universities abroad. UBMI provides doctoral students with a stipend and/or part-time in addition to the state stipend when participating in a grant project or participating in teaching.

   Tutor: Fohlerová Zdenka, doc. Mgr., Ph.D.

4. New approaches in recruiting bacterial genomes from metagenomes

   Recent advances in DNA sequencing allowed routine sequencing of environmental samples. However, current computational tools hardly keep up with constantly changing lab techniques and the growing output of sequencing devices. Therefore, novel computationally efficient techniques are needed to recruit particular genomes from metagenomes. The topic is focused on methods for recruiting particular bacterial genomes from environmental samples, i.e., metagenomes. While in the past all newly described bacteria had to be isolated and their culture had to be made publicly available, a recent initiative SeqCode brought a nomenclatural code for prokaryotes described directly from sequence data as many microbial species are uncultivable with current techniques. Moreover, even for newly published cultured bacteria, environmental evidence based on searching in publicly available metagenomes is nowadays required by scientific journals. Although tools to produce metagenome-assembled genomes exist, searching metagenomes for particular analysed genomes is done exclusively with BLAST and is not rigorously described. Unfortunately, due to the repetitive segments of bacterial genomes, false hits are always found and quantification of data, i.e., assuming an abundance of a genome in a metagenome, is therefore biased. The aim of the research is to find a method for quantification as precise as possible. The applied method will include specific steps to process short NGS as well as long TGS reads to cover all currently used sequencing technologies. The project will be solved mainly at the Department of Biomedical Engineering. However, cooperation with our national (University Hospital Brno, the Faculty of Chemistry BUT, and Czech Collection of Microorganisms) and foreign partners (Ludwig-Maximilians-Universität München in Germany and HES-SO Valais-Wallis in Switzerland) 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. 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: Sedlář Karel, doc. Mgr. Ing., Ph.D.