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Field
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between genetics and environmental factors in metabolic-related disorders using multiple innovative methodologies and large human biobanks. The project encompasses 1) Developing strategies to identify and
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• Proficiency in at least one statistical software (e.g., R, Stata, SPSS, Python) • Expertise in quantitative analysis, with preferred skills in o Quasi-experimental evaluation techniques (e.g., Difference-in
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: Experience in managing large-scale -omics data, including data storage, organization, and inventory across multiple platforms. Strong skills in record-keeping, facilitating data upload to online repositories
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to a global scale, targeting multiple oceanic bioprovinces to robustly quantify the alkalinization-attributable signal against natural carbon cycle fluctuations. The postdoctoral researcher will be
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distribution networks, considering solutions such as FL Energy's OperatorFabric.; - Study human-machine interaction methodologies that reduce the complexity of supervising multiple distribution networks
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python code) in developing the UK MRIO for a range of applications, whilst working alongside the wider research team in an inter-disciplinary environment. You will display a strong commitment to applied
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python code) in developing the UK MRIO for a range of applications, whilst working alongside the wider research team in an inter-disciplinary environment. You will display a strong commitment to applied
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data. Harmonize, curate, and provide customized datasets across multiple spatial and temporal resolutions tailored to specific research questions and stakeholder needs. Apply advanced statistical
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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techniques, methods, and research, especially deep learning literature, and how these methods apply to our use cases Ability to manage multiple projects and assignments with a high level of autonomy and