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mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. Experience in applying or developing machine learning
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corresponding knowledge in another way. A successful candidate should have excellent study results and a strong background in mathematics. The applicant should be skilled at implementing new models and algorithms
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relating this knowledge to plant health and sustainable plant protection is required. Previous experience in sampling, sequencing and analysing plant microbiomes, including bioinformatics and statistics as
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, biology (or related fields) with a focus on farm animal behaviour and welfare. interest and/or experience in animal behaviour, statistics, and computer-based data analysis. documented research experience
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desired. Knowledge on statistical methods and their application is an extra merit. Good knowledge in GIS and R is a merit. Proven excellence in written and spoken English is essential. The fieldwork will
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, quantification, and data analysis, including statistics. Variations of liquid extraction-based techniques, based on nano-DESI and electrospray ionization, will be developed further and coupled to modern mass
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spectrometry for molecular characterization of biological samples, using tandem mass spectrometry and reactive chemistry, quantification, and data analysis, including statistics. Variations of liquid extraction
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ecology, and/or restoration ecology. Experience in design, execution and analysis of acoustic data is desired. Knowledge on statistical methods and their application is an extra merit. Good knowledge in GIS
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applicant must have passed courses within the first and second cycles of at least 90 credits in either, a) Chemistry/Molecular Biology/Biotechnology, or b) Computer Science/Mathematics/Physics and at
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well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se/en/organisation/liu/ida You will be placed at the Human-Centred Systems division in the group of Knowledge