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relevant field (Informatics, Computer Science, Ecology, or Biology). strong Python programming skills proven experience with Machine Learning and image processing (Deep Learning/Object Detection) strong
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, playing a crucial role in forming the CREDO project as well as future research areas for the whole lab. MAIN JOB CONTENT Framework Collaborating with the project team (PI, 2 postdocs, 2 Phd students
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 10 days ago
operates the first Czech quantum computer named VLQ. For more details, see www.it4i.eu . Activity description: · conduct research in machine learning with emphasis on computer vision, · develop and evaluate
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 12 days ago
operates the first Czech quantum computer named VLQ. For more details, see www.it4i.eu . Activity description: · conduct research in machine learning with emphasis on computer vision, · develop and evaluate
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. Approaches researched: molecular dynamics, quantum simulations, machine learning/AI, and high-throughput computing. Required: Mgr./MSc. in chemistry, physics, computer science, or a related field If you are
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professionals (such as PhD or postdoc supervisors) who can provide reference. Please submit your application to email: recruitment@biomed.cas.cz and make sure to include this identification code: Scientist
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 30 days ago
systems Computer science » Informatics Information science Information science » Information management Researcher Profile Recognised Researcher (R2) Application Deadline 31 Mar 2026 - 12:30 (UTC) Country
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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