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: A Master’s degree (or will graduate before appointment date) in Ecology or Environmental Science; Strong statistical analysis and technical skills; Proficient in the application of spatial analysis in
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piezoelectric composites and material architecture to achieve improved electromechanical coupling and spatial resolution would be important. In addition, they should have experience in sensor array readout
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chemistry) laboratory; statistical skills for proper data treatment ; experience with programming (R or Python) for data handling and visualisation; strong analytical skills; excellent communication skills
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genomic, transcriptomic, epigenetic, proteomic, digital spatial, and other ‘omics data in healthy and disease states close interaction with the bioinformatics and immunology teams of Katrin Kierdorf, Julia
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qualifications Masters degree in a relavent scientific field, such as biology, ecology, or natural resource management Experience conducting field work Basic statistical competence The following experiences and
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flowering times over large spatial scales. Now, the PollenNet project seeks a highly motivated PhD student working at the interface of plant phenology, citizen science and ecological modelling. The PollenNet
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PhD Position on Unravelling the Social Exposome for Better Health Faculty: Faculty of Geosciences Department: Department of Human Geography and Spatial Planning Hours per week: 36 to 40
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., health and climate/environmental data) and could include a range of data science methods, such as utilising geographical information systems (GIS), statistical analysis, machine learning, deep learning
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requirements are Experience in working with large-scale spatial-temporal traffic and/or travel behavior data, e.g., loop detector, floating car data, GPS data, cellphone data. Experience with transport
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) Proven affinity with the application of statistical methods for data analysis of spatial and temporal datasets in the domain of agronomy, ecology and environmental sciences Proven affinity with modeling