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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning
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analysis, or data science); a genuine enthusiasm for the ocean and marine sustainability challenges; a strong motivation to advance the field of environmental and natural resource economics; strong
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the World Wide LHC Computing Grid. The successful candidate will work primarily with pixel detectors construction, and electrical test-systems, and to some extent with test beams, data analysis and
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extended from cloud solutions (such as OpenLLMetry), the research question is how to identify anomalies in collected information that can come from multiple AI services either invoked manually by users or by
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an interdisciplinary team; Vegetation surveys, soil physical monitoring and carbon flux observations; State-of-the art analysis of spatio-temporal and ecological data; Collaboration with researchers and (BSc/MSc
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strain engineering is a plus. Data analysis skills (e.g. in Python, MATLAB or similar) are a plus. Excellent communication skills in English, both written and spoken Strong motivation to work
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powerful ideas and tools at the intersection of topological band theory, symmetry analysis, and photonics. You will work on developing and applying these ideas to discover new topological phenomena, design
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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter
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will focus on the development and application of innovative methods for data-analysis and integration, including AI based methods to combine the different types of data, using data from different case
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peer-reviewed publications Preferred Qualification Familiar with various chemical analyses and characterization instruments Experience in process modeling using Aspen or other software and TEA analysis