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phenological data using camera and drone-based imagery. Use genetic analyses to assess the relationship between genetic differentiation and phenological variation. Develop and implement advanced statistical
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patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which
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DTU Tenure Track Researcher in Nutrition, Sustainability and Health Promotion with a focus on Sus...
xperience with quantitative research methods, Experience in reproducible statistical analyses (preferably R and Python) and in the peer-reviewed publication of results. Must be able to work interdisciplinary
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Are you interested in human health and big data collaborative projects at the cross road of genomics, population genetics and statistical learning then the Bioinformatics Research Centre at Aarhus
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. Measurement techniques in field applications and in the laboratory. Modeling and simulation skills (batteries, energy systems, electric equivalent circuits). Machine learning, statistical analysis, and other
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Assistant (tenure-track) and Associate Professor positions in Data Science at the Department of M...
are looking for Hired candidates will join the Data Science and Statistics Section and the new SDU Centre for Computer Science and Artificial Intelligence in Campus Vejle. We encourage applications from
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Tenure-Track Assistant Professor / Associate Professor in Bioinformatics at Aarhus University, De...
our current research portfolio and teaching activities. We welcome applicants within all areas of bioinformatics with a strong focus on development of computational and statistical methods, particularly
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familiar with marine ecosystems, the deep biosphere or marine microbiomes and the necessary bioinformatic and statistical analyses of such data (e.g. taxonomic assignments, gene prediction, phylogenetics
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quantitative microbiology and model development Documented skills within quantitative and statistical analysis of complex datasets Documented experience in experimental food microbiology Experience with
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applications Experience in managing data and model simulation Insight into applied statistics and spatial data Experience with collaborative data project infrastructure Who we are At the Department