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- Faculty of Science, Charles University
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preparation and testing or powder mixtures, and then to devise predictive models (possible using machine learning approaches) for the estimation of mixture properties from pure component propeties. The PhD
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implementing state-of-the-art AI-powered models for the automated taxonomic identification of insects captured via high-resolution camera traps. You will build upon the prestigious SEPPI Biodiversa (Standardized
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Republic (www.fgu.cas.cz/en ) Funded PhD student positions are available at the Institute of Physiology CAS (IPHYS) in Prague in the Czech Republic in: NEUROSCIENCE METABOLISM CARDIOVASCULAR PHYSIOLOGY IPHYS is one
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Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences | Czech | 2 months ago
Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We are seeking a highly motivated PhD student to join our
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) Positions PhD Positions Application Deadline 15 Mar 2026 - 23:59 (Europe/Prague) Country Czech Republic Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Jun 2026 Is the
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by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Position Overview The open PhD positions will be involved in mostly experimental research
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postdoctoral candidates with background in social psychology, cognitive science, or social neuroscience to join a highly interdisciplinary project on the computational model of decision-making. The Computing
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glioblastoma therapy From neurons to behavior: mechanisms of cognitive deficits in animal models of brain disorders Impact of gestational diabetes management strategies on breast milk composition and early
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by metal nanoparticles, cell survival and radioresistance. The MS-RADAM research programme combines state-of-the-art computational multiscale modelling (using DFT/TDDFT methods, collision theory
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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