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You will focus on: Studying the slug stability of organic solvent slugs (e.g. acetone, acetonitrile, chloroform) in different push solvents for detection of apolar metabolites with segmented flow NMR
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modelling. Experience in analysing ecological monitoring data (e.g. telemetry, diet and population datasets). Advanced programming skills (R, Python, or equivalent) and reproducible analytical workflows (e.g
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the electromagnetic spectrum and studying problems at different scales, from molecular processes in clouds to global environmental change. Our research environment is unique in Sweden, combining expertise in
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employees, whose jobs are being replaced by digital technologies. The Lab partners with organizations to test the feasibility, scalability, and effectiveness of different approaches to the skills challenge
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an experimental technique. Experience with lab planning and maintenance. Experience with data analysis using, e.g., Origin, Python or MatLab. Programming skills, e.g. proficient with Labview or Python. All
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collected as part of current CIHR funded project “Sex differences in brain aging in adults with and without risk factors for Alzheimer’s Disease” which focuses on midlife, and examines the effect of menopause
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must be performed, with particular attention paid to certain critical areas, such as the warm/cold interfaces and the BCOM beam separation magnet. In this critical area, three beams of different energies
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modelling. Experience in analysing ecological monitoring data (e.g. telemetry, diet and population datasets). Advanced programming skills (R, Python, or equivalent) and reproducible analytical workflows (e.g
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key elements to answer the question of the causes of changes in ozone trends throughout the troposphere. This will involve exploring regional and vertical differences to better understand the dominant
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University of Strasbourg (UMR7178), is a multidisciplinary laboratory where research teams from different scientific cultures (ecology, physiology and ethology, chemistry and subatomic physics) develop very