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11.07.2022, Wissenschaftliches Personal The professorship “Big Geospatial Data Management” is seeking to fill two research assistant (E13) positions to support research activities around geospatial
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using experimental data from laboratory setups Validate models through targeted measurements and structured testing procedures Analyse loss mechanisms and system efficiencies under various operating
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environment of the institute. Opportunities Access to a unique and comprehensive dataset combining genomic and clinical information from a large cohort of cancer patients. Potential to establish an independent
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | about 3 hours ago
candidate has excellent quantitative and data analysis skills, a proven ability to work independently, and a collaborative mindset. They will be expected to lead their own research projects, contribute
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large multi-dimensional datasets using statistical tools such as positive matrix factorization (PMF) and cluster analysis Investigate the influence of different urban emission sectors on atmospheric
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invasive sensing tools to monitor metabolites, oxygen, carbon dioxide, pH, and other parameters. Ideally, the methods can function in parallel and on a large scale. The research is vital to understand key
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scale and the coastal areas, up to, and including, development and demonstration of climate services. RIVIERADE will target three European Seas (Baltic, Black, Mediterranean), to produce data and
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computer scientist with programming experience, but no background in science communication - or vice versa - we still encourage you to apply. Your tasks and duties will be a subset of the following
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to contribute to tackling one of the big challenges of our time – then you may want to apply to the position in our team, which is expected to start on 01.11.2025. Appointment is conditional on approval by
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scientific journals and conferences Your Profile: A doctoral degree in Physics, Materials Science, Computer Science, Data Science, or related fields Proven experience with large language models (LLMs), natural