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identification, i.e. learning of models from measured data, and iii) real-time control, e.g. using the model predictive approach. We are working on several projects with industrial partners across the energy
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programs at the Faculty of Horticulture, aiming to acquire the theoretical and practical knowledge necessary for mastering professional studies. The teaching is primarily focused on issues related
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educator in statistics and/or modern data analysis (including ML/DL). Research scope – expertise in any of the following areas • statistics, data analysis, and information theory, • machine learning, deep
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or equivalent Skills/Qualifications - university degree in a technical field - ability to work with softwares MS Teams. CAD, etc.; - responsibility, active task solving and willingness to learn new things
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to climate change and variability Hydrological processes in organosols and peat-affected soils Modeling Hydrological Extremes Using Machine Learning Spatial and time distribution of precipitation within
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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
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antibodies and anti-CD20 CAR T-cells form the backbone of treatment for mature B cell malignancies. The project focuses on elucidating changes in gene expression within the tumor microenvironment of chronic
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Machine Learning. Profile of the graduate The graduate displays deep theoretical knowledge in molecular and cell biology, genetics and virology, with focus on some specific branch of these scientific fields
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, or related fields Theoretical and experimental knowledge in the field of wave and geometric optics Interdisciplinary focus, ability to quickly acquire new knowledge and skills, communication with colleagues
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process Access to sports facilities on campus For more information about the PhD program and the advertised PhD projects visit: https://fgu.cas.cz/en/students-and-career/ph-d-studies/ How to apply? PhD