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models for multiple chronic diseases in real-world data and cohort studies. To successfully work in this position, experience of data-driven analytical approaches, machine learning and advanced
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complex chemistry, molecular metal compounds, homogeneous metal catalysis, organic synthesis, mechanochemistry of metals, as well as experience in analytical techniques including NMR, PXRD, HRMS and ICP-MS
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the research area of the project. Demonstrated quantitative and analytical skills, including programming or modelling experience. Ability to work both independently and as part of a multidisciplinary team
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perception at the landscape scale under different scenarios and employ behavioural experiments and Big Data analytics to understand how changes in time perception influence pro-environmental and sustainable
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scenarios and employ behavioural experiments and Big Data analytics to understand how changes in time perception influence pro-environmental and sustainable behaviours. NATURETIME aims to generate actionable
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of a highly experienced and enthusiastic research team and Unit, with whom you can share and develop your expertise Career development and learning opportunities in a multidisciplinary, international
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including high-impact scientific publishing, and collaborative research with international teams. Who we are looking for Requirements MSc degree in Computer Science, Data Science, Machine Learning, or a