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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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verifiable, data-driven post-mortem analyses of agricultural disasters. Your duties and responsibilities include: Conduct research on state-of-the-art Causal Machine Learning for the Earth Sciences
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)”, funded by the Swiss National Science Foundation. Focusing on case studies in the Netherlands and Switzerland, the project aims to better understand urban densification as a contested process of land rent
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The climate and biodiversity crises make it urgent to rethink how we manage land and water. Current land-use systems are often eroding the ecological foundations on which long-term prosperity depends. Existing
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land use pressures obtaining land for nature restoration may be difficult and may involve resistance. In other locations the added value of restoration may be smaller. Having insight in the spatial
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Switzerland, the project aims to better understand urban densification as a contested process of land rent creation and redistribution, thereby exposing tensions among actors, values, discourses, and
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First Stage Researcher (R1) Application Deadline 15 May 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU
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17 Apr 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Physics » Biophysics Physics » Statistical physics Researcher Profile First Stage Researcher
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challenging organisation. The Faculty of Geosciences is organised in four Departments: Earth Sciences, Human Geography & Spatial Planning, Physical Geography, and Sustainable Development. The team
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PhD Position in Statistical Physics & Data-Driven Viral Evolution Faculty: Faculty of Science Department: Department of Physics Hours per week: 36 to 40 Application deadline: 23 April 2026 Apply