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, including the programming, AI – tools, machine learning Residence outside the Czech Republic Nice-to-have: Prior experience with microscopy and plant research Experience living or visiting Czech Republic and
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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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of dissertation topics: Developing Remote Sensing–Based Indicators of Landscape State and Change Using Data-Efficient Machine Learning Across Scales Profile of the graduate The graduates have deep theoretical
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of Central and Eastern Europe Political and regional geography: issues and approaches Private Military Companies as Geopolitical Agents: Their Role in Constructing Security Discourse Variegated Urbanisation
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of dissertation topics: Development of Machine Learning Frameworks for Reactive Atomistic Materials Modeling (DSP II) Profile of the graduate This Ph.D. program is an interdisciplinary study combining physical
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or organometallic synthesis is familiar with structure elucidation techniques is independent, proactive and eager to learn new methods Fluent English is required; knowledge of Czech is not necessary. What we offer a
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. The successful candidate will acquire skills in cluster analysis, joint inversion, geophysical-petrological modelling and tectonics, will do research visits in Kiel University and participate in
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independently and work with scientific literature Good communication skills in English (written and spoken) No fear of bees. We will teach you everything else… Previous experience with bees is still very welcome
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systems, cartography, and remote sensing. Students acquire theoretical and practical knowledge, methodologies, and techniques for solving geographical problems. It encompasses scientific research and