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. energy, water and sanitation, mobility or food) in European and Indian cities analyse the material using qualitative process methods (path tracing) and semi-quantitative network methods (socio-technical
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at both local and global scales, and contribute to the Thermal Ecology Alliance. Therefore, the PhD student will have excellent opportunities to develop a large collaborative network and address broad
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collaborative network and address broad questions in global change biology. The projects will be primarily supervised by Patrice Pottier, and co-supervised by Prof. Fredrik Jutfelt at the University of Gothenburg
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utilization. Duties The PhD student will participate in all stages of the research process. Duties include planning and conducting feeding trials with dairy cows, sampling and analysis of biological materials
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Institute of Neuroscience and physiology, Sahlgrenska Academy, university of Gothenburg | Sweden | 25 days ago
fluid and cognitive measures, for early detection, disease staging and prediction of progression. The project is embedded in an international supervisory network spanning Gothenburg, Stockholm, Barcelona
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nutrition, such as: analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and
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applications in different project contexts. This may include data analysis, modelling, literature reviews, and interaction with relevant stakeholders. The results are expected to contribute increased knowledge
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computing using clusters like UPPMAX and GPUs for high-performance computing are essential. While not required, experience in genetic and omics data analysis and visualization, and familiarity with network
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, geoinformatics, oceanography, or a related field as well as good knowledge in written and spoken English is a requirement. Merits are: Experience with environmental data analysis and quantitative methods, with
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machine learning approaches, particularly neural networks, and experience with workflow management systems (e.g., Snakemake, Nextflow). Knowledge of transcriptomics and alternative splicing analysis