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the consequences of climate change and strengthen the resilience of mountain areas. The thesis will be based on a multidisciplinary approach combining statistical analysis, level-meteorological modeling, and machine
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Corruption and institutional trust (expected level: high) • Practical expertise in open science practices (expected level: very high) • Team coordination (expected level: high) • Statistical data analysis and
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required: The candidate should have a strong interest in evolutionary genomics and ecology; should be willing to acquire an extensive training in bioinformatics and statistical data analysis; should have
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markers, flow cytometry, and cell sorting. • Generation and analyses (bioinformatic and statistical) of environment and microbiome data, including amplicon sequencing libraries, metagenomes, and
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, Communication, Optimization • SyRI: Robotic Systems in Interaction The PhD student will join the CID team, whose research focuses on Artificial Intelligence, including statistical learning, uncertainty management