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PhD position: Global soil mapping with process-informed machine learning Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline
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background in hydrology, earth system science, atmospheric science, agroecology or other appropriate fields. You will work on the project “Physics-informed AI-modelling of land surface processes in a global
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and understanding of complex biological systems and biodiversity. You will get the opportunity to learn about both simple and complex biological models, computer programming, data visualisation, and
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part of the Software Technology group . Research in this group focuses on using and improving functional programming languages such as Haskell and Agda, in particular for parallel computing, software
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, including biodiversity conservation, carbon sink, energy production, fisheries, aquaculture, transportation, and tourism. Proponents emphasize the benefits of a diversified blue economy for achieving multiple
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multiple transitions in the built environment by aligning values , and collaborate with a wide range of interesting stakeholders, specifically in the field of the built environment. You will also be involved
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-develop practical approaches through workshops and working sessions. You will embed yourself in ongoing change processes and help collectives envision and develop the organisational and digital tools
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School of Economics. Your qualities We are looking for a talented researcher with passion for applied research, who meets multiple of the following requirements: a Master’s degree in economics or a related
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predictive theory for rapidly evolving viruses. You will work at the interface of theoretical physics, stochastic processes, statistical inference, and epidemiology, with SARS-CoV-2 and influenza as key case
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in the intellectual life of the research group, including seminars, reading groups, and collaborative writing processes. Where to apply Website https://www.academictransfer.com/en/jobs/359450/phd