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based on machine learning. Reference number 08/26 Your tasks 1. Assessment and analysis of GaN technology characterization data Identification of outliers during testing, with and without machine learning
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interdisciplinary project seeks to develop new approaches to resilient and sustainable urban development, in cooperation with Karlsruhe Institute of Technology (KIT) and RWTH Aachen. For the subproject based
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The Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB) is a pioneer and a driver of bioeconomy research. We create the scientific foundation to transform agricultural, food
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physics, engineering, environmental sciences, or a relateddiscipline, is required. Basic knowledge and initial experience with experimental working methods (e.g.spectroscopy, laser physics) Fundamental
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Qualifications / Experience: A PhD degree in physics, engineering, environmental sciences, or a related discipline, is required Knowledge and hands-on experience with atmospheric lidars or other atmospheric
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of aerosol research with in-depth experience in measurement technology and quality assurance for the Department of Atmospheric Microphysics (AMP). In addition to research activities, the position encompasses
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command-line environments (including remote systems via SSH) and Windows interest in modern software engineering practices (testing, code review, modular design) fluency in English as working language What
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The Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB) is a pioneer and a driver of bioeconomy research. We create the scientific foundation to transform agricultural, food
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funding activities in the field of research data management or software engineering Our requirements: University degree in computer science, chemistry, physics, mathematics or engineering, completed PhD in
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methodological approaches to law, economics, and finance while they complete their thesis. Requirements and expectations Applicants must have completed a law degree with honors (top 15%) at a research university