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processes with relevance for irrigation and drainage Have knowledge in programming in R and Python for statistical analyses and modelling. This includes experience in applying these skills in projects Have
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, undergraduate and postgraduate education in communications engineering, statistical signal processing, network science, and decentralized machine learning. Welcome to read more about us at: https://liu.se/en
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and the ability to develop and conduct high-quality research relevant to the position. The applicant must demonstrate knowledge of statistical methods, documented experience of ethnographic fieldwork
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analysis, and greenhouse experiments. Analyse ecological and evolutionary data using appropriate statistical methods Collaborate with an interdisciplinary research team and contribute to group discussions
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Python for scripting and data analysis, metabolite ID via MS/MS and annotation (e.g. SIRIUS, HMDB, authentic libraries etc.), statistical uni- and multivariate analysis, data visualization (PCA score
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MS/MS and annotation (e.g. SIRIUS, HMDB, authentic libraries etc.), statistical uni- and multivariate analysis, data visualization (PCA score, volcano, heatmap, and correlation plots, either software
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, statistical data analysis (e.g., linear models, linear mixed models, genomic prediction, genomic association studies, etc.), analysis of genotype and DNA sequence data, simulations programming/scripting
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spectrometry or alternatively structural biology. Knowledge in data analysis and statistics. Strong ability to communicate effectively in English, both orally and in writing. Documented experience in scientific
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include animal breeding, population genetics, genetic diversity, statistical data analysis (e.g., linear models, linear mixed models, genomic prediction, genomic association studies, etc.), analysis
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statistics, cognitive science and innovative programming. Read more at https://liu.se/ida You will be funded by and will join ELLIIT (Excellence Center at Linköping–Lund in Information Technology), a research