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, economics, statistics, public health, or medical sciences, or have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including an independent project worth
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/southern Sweden and potentially other locations (> 8 hours drive from Umeå). Other meriting qualifications are: Strong quantitative skills, with experience in statistical modeling or spatial data analysis in
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: Analyze spectroscopic and kinetic data, employ statistical and machine learning approaches where relevant, and contribute to manuscripts, presentations, and reports. Collaboration: Work closely with project
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the field and in the lab) and developing scientific publications. We expect them to be pro-active and take own initiatives. Good numerical and statistical skills and some previous experience in molecular
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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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, 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