27 image-processing-"Gustave-Roussy-"-"Gustave-Roussy-" PhD positions at Utrecht University
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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 Earth Sciences or another appropriate field. You will work on the project “Nanoscale Rock Magnetism and Magnetic Imaging”. Your job This study is part of the ERC Consolidator project SPARK, which
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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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groups, and collaborative writing processes. Your qualities The ideal candidate for this PhD position must have: a Master’s degree in a relevant scientific discipline in the Humanities or Social Sciences
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these signals with their transcriptional programs. You will use a variety of techniques and tools, including microscopy and fluorescent imaging techniques, transcriptomics, metabolite profiling and high
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3 Apr 2026 Job Information Organisation/Company Utrecht University Research Field Computer science » Cybernetics Computer science » Programming Engineering » Computer engineering Engineering
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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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physics, stochastic processes, statistical inference, and epidemiology, with SARS-CoV-2 and influenza as key case studies. Your job In this project, you will develop a quantitative theory of evolution
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approached as a situated process emerging through the interaction of data, models, professional judgement, and organisational context. Depending on your interests and empirical setting, the project will
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decision-making and reinforcement learning Enhancing transparency and contestability of decision-making processes, taking a multimodal approach to reveal the reasoning behind complex AI-driven planning and