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Field
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of extensive datasets. You will be supervised researchers who collectively offer expertise in computational biology, genetics, epidemiology, and machine learning. The research will be closely linked
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is to advance the understanding of forest ecosystems and how these should be managed today and in the future. For more information: http://www.slu.se/en/departments/forest-ecology-management/ Read more
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access to preventive care and neighborhood characteristics influence long-term health trajectories. The project applies both econometric and machine learning approaches to identify high-risk groups and to
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complex systems. Development and application of theoretical tools that combine experimental data and atomistic computer simulations to provide a comprehensive picture that is difficult to achieve through
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today and in the future. For more information: http://www.slu.se/en/departments/forest-ecology-management/ Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about
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) , was created. The Department of forest genetics and plant physiology is part of Umeå Plant Science Centre (UPSC, https://www.upsc.se ) which is a centre of excellence for experimental plant research and forest
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undergraduate and advanced levels, mainly in programmes leading to degrees in agronomy and biology. Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu
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programmes leading to degrees in agronomy and biology. Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Perennial cropping systems Research
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series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamic systems is
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the research and teaching environment at the department, as well as in the everyday activities of the project, including reporting to FORMAS. More information about the project: https://portal.research.lu.se/en