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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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management knowledge into relevant research designs; developing research questions; applying appropriate econometric and qualitative analytical tools; writing scientific manuscripts and compile a Ph.D. thesis
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and develops a wide range of topics related to chemical hydrogen storage along the entire process chain. We place a particular emphasis on LOHC technology, addressing issues across different scales. Our
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geospatial data on fisheries activities near OWFs to evaluate the distributional impacts of OWFs across different fleet segments; conducting fieldwork and surveys in collaboration with ‘NO REGRETS’ partners
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Cadence Virtuoso, Spectre, or Mentor Graphics. Understanding of semiconductor device physics, especially MOSFET operation, modeling, and scaling. Strong analytical and problem-solving skills, with
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Ability to work independently as well as in teams. Work in a structured way, set goals and make plans to achieve them, result-oriented. Excellent analytical skills, analyze data, assess different
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architectures, and on-device inference on edge-compute platforms. Demonstrated analytical problem-solving through experimental design, critical quantitative and qualitative data analysis, and validation
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testing, to achieve sub-second cycle times for robotic systems. 3. Demonstrated analytical problem-solving through experimental design, critical quantitative and qualitative data analysis, and validation
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modeling, optimization, and/or data analytics. Description of the PhD topic (subproject C1 - New metrics for transportation system appraisal): Transportation systems must deliver “function” (i.e
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understanding of the process, statistics and data analytics shall be applied to link the different conditions to the likelihood of microcracks occurring. The severity of microcracks may also be studied in