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, geometallurgy or related field Experience in either stochastics, deep learning or minerals processing is needed Structured and solution-oriented working style, analytical thinking and above-average committment
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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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with chemoreception and sensory biological techniques (SSR, GC-EAD, EAG). •Experience in analytical chemistry (GC-FID, GC-MS). •Experience in or willingness to learn statistical data analyses, data
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microscopy Experience in cell sorting via FACS and experimental lung research would be advantageous Extraordinary level of autonomy, initiative, analytical thinking and ability to work in a team Excellent
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under civil law in Freising, is a research institution of the Leibniz Association that combines methods of biomolecular basic research with analysis methods of bioinformatics and analytical high
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science and energy technologies Basic knowledge of artificial intelligence and data analysis methods Programming skills, ideally in Python Independent and analytical way of working Reliable and thorough
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or very-good university degree in economics, business studies, agricultural sciences with a focus in economics, or related disciplines strong analytical and methodological skills with a focus on
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, very good verbal and written English communication skills. What we offer: Pioneering Research Environment: Shape
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the RTG. General Requirements: We are looking for first-class graduates with expertise in the RTG-addressed PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, very good