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Field
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simulations, computational modelling, and/or data-driven analysis to assess the impact of different climate policy pathways. Developing interactive AI-based narratives that communicate climate risks in ways
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to the development of technology to create sustainable and circular solutions for products and services with applications in the environment, analysis, food, water, agriculture, medicine, and industrial biotechnology
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ability to work effectively both independently and in a team environment Merits: Experience in method development, working with spatial data, and GIS Experience with univariate and multivariate analysis and
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, Sweden, and the Netherlands, collaborating on qualitative, ethnographic research and data analysis. Duties include: Planning and conducting field studies and interviews in Sweden, Finland, and/or
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, hydrology, environmental analysis, and physical geography. More information on the programme’s science can be found at Luval. Duties The project focuses on the investigation of zonal jets in planetary
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research activities, contributing to data collection and analysis, preparing reports or documentation, and collaborating closely with faculty, researchers, and students in relevant projects. This position
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(or equivalent) in Computer Science, Statistics, Ecology, Biology or Forestry. · Documented experience with application of deep learning and advanced statistical analysis and programming (e.g., R or Python
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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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transcription initiation and termination during several years in growing spruces and pines that are exposed to stress. The project includes both wet lab work and bioinformatic analysis. With our research, we will
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, multiplex secretion analysis, high throughput cell phenotype screening, in vitro cultures of WAT-resident cells as well as standard molecular biology techniques to functionally characterize the interaction