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Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences | Czech | 2 months ago
their molecular organization remains poorly understood. This PhD project will address this fundamental question by focusing on IWS1, a conserved transcription elongation factor that functions as a central
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was the focus of their doctoral studies, and they are familiar with modern methods in the field, especially anatomical, physiological, and molecular ones. They have become a distinctive scientific personality
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cellular level. They involve developing analytical methods and software tools for large, domain-specific, and heterogeneous data to understand cellular processes and apply findings in medicine and
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-environmental and geographical situatedness of work environments in the ancient Roman Empire contributed to the spatial spread of ancient cults. Using computational methods, the project examines how
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) Expected workload: 100 % (or by agreement) Job description: teamwork on the development of new methods for the detection, separation, and quantification of biochemically significant molecules using
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research and applications of advanced spatial data analysis methods, data collection, and interpretation of remote sensing data, database system theory, mapping, spatial data distribution, development of new
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research. Using field and qualitative methods research, historical sources and modern geoinformatics technologies, the student will be able to reconstruct, understand and interpret the developments
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potential of classical and innovative fertility forecasting methods in the context of the Czech Republic Profile of the graduate In addition to the scientific and pedagogical pathway at universities, a
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activities focused on professional, impact factor-ranked journals, books and book chapters, patents, utility models, implemented technological components, and other outputs of applied research. UCT Prague
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and migrations of ancient humans in Eurasia; Other ongoing projects in the Laboratory of archaeogenetics, such as testing and improvement of analytical methods such as PCA and manifold learning