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, associate or full professor) in teaching and research, with an expected start date of August 2026. Applicants must hold a Ph.D. We welcome scholars whose expertise engages geographical/spatial issues across
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sustainability. The candidate will develop and apply spatial analysis, remote sensing, and modeling to evaluate the technical, environmental, and socioeconomic implications of transitioning to resilient crops in
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multidisciplinary experience in combining integrative computational immunology – data-driven, state-of-the-art single cell resolution and spatial methods, machine learning and kinetic modeling – with integrative
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for low-frequency railway vibrations—bridging experiments, modelling, and sustainable railway innovation. Interested? Job description TU Delft, in collaboration with ProRail and Cohere Consultants, invites
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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supporting methods and models that support the plan development and implementation process. Urban planning is closely related to transportation planning. The change in the spatial distribution of demand and
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and tourism. The recruited person will carry out the following tasks: • Application of distributed hydraulic and hydrological models to simulate water behaviour and sediment transport in the pilot
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comprehensive training aimed at building essential scientific and transferable skills. Job Duties: Implementation and bioinformatic evaluation of transcript- and protein-based spatial single-cell multi-omics
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adaptation, and infrastructure resilience. This project will tackle that challenge by developing a new blended UK precipitation dataset at high temporal (15-minute) and spatial resolution. The student will
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computational biology research, in particular in single cell and spatial domains, applying AI/ML models in translational or clinical research. Project Leadership Experience: Demonstrated ability to manage complex