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Bioinformatics
Doctoral Programme,
Faculty of Chemical Technology
The aim of the DSP programme is to educate specialists in bioinformatics, which is a combination of molecular and cell biology, biochemistry, statistics and computer science. Bioinformatics deals with the development of tools for the management of biological databases, algorithms for the processing of molecular-biological data and methods for the analysis and interpretation of relationships in these data. Most of the projects are biologically oriented with the aim to understand the complex context in the studied biological phenomena. However, we also run IT-oriented topics that include the development of algorithms or data processing methods. CareersThe combination of the education in natural sciences and informatics qualifies graduates to work in interdisciplinary teams. Graduates will find employment in a wide range of areas where data obtained by instrumental analysis of biological samples are processed. Graduates can also rely on a broad knowledge of informatics and can be successful in the development of software technologies, especially for data analytics. Graduates will further find employment in scientific infrastructures built in the Czech Republic within the framework of European operational programs. Due to the persisting lack of experts with an interdisciplinary education, graduates will also be easily employable outside the Czech Republic. Typical positions that DSP Bioinformatics graduate can hold: - researcher in basic or applied research in the public or private sector in the fields of biomedicine, clinical medicine, medical and pharmaceutical chemistry, food, agriculture, biotechnology or forensic science. Typical positions are postdoc, programmer, research associate, research fellow, project leader, project manager. - university lecturer in bioinformatics, computational biology, computational chemistry or applied informatics. Typical positions are assistant professor, assistant, lecturer. - software developer or data analyst in IT companies. - professional positions that require organizational and analytical skills and expertise not only in bioinformatics. Typical job positions include state administration at the highest management levels, organizations that are methodologically and organizationally engaged in science and research or non-profit and educational organizations. Programme Details
Ph.D. topics for study year 2024/25Machine learning in biochemistry
AnnotationOur lab combines cutting-edge experimental (e.g., LC-MS, metabolomics, RNA-seq) and computational (e.g., bioinformatics, molecular networking, machine learning) approaches to develop rapid, generally applicable workflows for the discovery and utilization of bioactive molecules derived from plants. The successful candidate for this position will be developing machine learning models for the prediction of enzymatic activities of enzymes in specialized biosynthetic pathways.
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Study place:
Institute of Organic Chemistry and Biochemistry of the CAS
Drug discovery with explainable artificial intelligence
AnnotationThe PhD project focuses on the application of explainable artificial intelligence (XAI) in the field of computer-aided drug design. It aims to develop new methodologies that make the decision-making processes of AI models in drug discovery more transparent and understandable. The project will explore how XAI can improve the reliability of predictive models used for identifying potential drug candidates. A significant aspect of the research will involve integrating XAI approaches with existing drug design algorithms to enhance their interpretability. Ultimately, this project seeks to bridge the gap between advanced AI techniques and practical pharmaceutical applications, fostering more efficient and informed drug development.
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Study place:
Department of Informatics and Chemistry, FCT, VŠCHT Praha
Molecular mechanisms of the environmental stress response in model cell systems
AnnotationEnvironmental pollution represents a global problem affecting health of most of the population worldwide. To effectively protect the organism against negative impacts of environmental pollution detail molecular mechanisms of effects of pollutants need to be revealed. The aim of the thesis is to evaluate the impact of air pollution of whole-genome mRNA expression and epigenetic mechanisms (miRNA expression, DNA methylation) in model human cell systems in vitro. Lung and olfactory mucosa tissue models will be exposed to ambient air in localities with different levels of environmental pollution and mRNA expression profiles and epigenetic changes will be evaluated. The thesis should contribute to formulation of a detailed model describing, at molecular level, the response of the organism to ambient air pollutants.
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Study place:
Institute of Experimental Medicine of the CAS
Ancient DNA population genomics: detection of population substructure in human populations
AnnotationThe development of ancient DNA (aDNA) technologies in recent years gave rise of vast number of human genomic samples, especially from the prehistorical Europe. Most of the known samples are coming from the first four millennia before CE, a periods described as Neolithic, Bronze Age and Iron Age epochs based on associated archaeological findings. These populations are described primarily using their cultural features (archaeological findings, e.g., pottery, burials, food production, technology). The biological relationship between different populations living at that time are only beginning to be unfolded. The applicant will assist in bioinformatic processing of aDNA genomic samples (within an awarded CZ-PL Weave international grant project), focusing on populations from Bronze and Iron Age period from central Europe. The obtained genomic data will be utilized in the main goal of the proposed PhD project – to test different methods of detection of the population substructure and similarities, and identification of population admixture or isolation events. The applicant will be encouraged to test various population genetics methods, as well as modern dimensionality reduction and machine-learning techniques and approaches to describe and comprehend the genomic data on population level. This should allow us to better recognize the genetic background of the target populations, estimate the gene flow between them and thus the regional variability, and help us ascertain their social structure, marriage patterns and identify possible migrations.
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Study place:
Institute of Molecular Genetics of the CAS
Advancing Drug Design with Artificial Intelligence and Nuclear Magnetic Resonance
AnnotationIn this industrial PhD project, the candidate will join a dynamic team at the intersection of Cheminformatics, Artificial Intelligence, and NMR, focusing on Drug Design. The role involves enhancing AI|ffinity's NMR-AI platform components for virtual screening, hit discovery, and lead optimization. This task includes developing innovative software solutions for one or more of the following applications: 1. Enhancing 2D molecular representations to bolster the accuracy of ligand-based virtual screening, utilizing 1D NMR screening spectra. 2. Improving AI-driven, structure-based lead optimization algorithms, harnessing the power of 1D NMR restraints. 3. Innovating in de novo drug design algorithms by leveraging ligand epitope information from 1D NMR screening experiments. The project offers practical application of these tools in real-world drug discovery, in collaboration with AI|ffinity and its partners, and includes an international industrial internship for global exposure and insights, directly contributing to drug development.
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Study place:
Department of Informatics and Chemistry, FCT, VŠCHT Praha
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Updated: 21.1.2022 15:24, Author: Jan Kříž