Department of Informatics and Chemistry

Granting Departments:	Department of Informatics and Chemistry
Study Programme/Specialization:	Bioinformatics ( in English language )
Supervisor:	prof. Mgr. Daniel Svozil, Ph.D.

Annotation

In 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.

Granting Departments:	Department of Informatics and Chemistry
Study Programme/Specialization:	Bioinformatics ( in English language )
Supervisor:	Ing. Martin Šícho, Ph.D.

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The 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.

Institute of Experimental Medicine AS CR, v.v.i.

Granting Departments:	Department of Informatics and Chemistry Institute of Experimental Medicine AS CR, v.v.i.
Study Programme/Specialization:	Bioinformatics ( in English language )
Supervisor:	RNDr. Pavel Rössner, Ph.D.

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Environmental 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.

Institute of Molecular Genetics of the CAS, v. v. i.

Granting Departments:	Department of Informatics and Chemistry Institute of Molecular Genetics of the CAS, v. v. i.
Study Programme/Specialization:	Bioinformatics ( in English language )
Supervisor:	RNDr. Edvard Ehler, Ph.D.

Annotation

The 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.