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climate control to direct crop-centric control. This paradigm shift relies on breakthroughs in microclimate sensing, interpreting crop performance by integrating sensor data at different temporal and
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validation, experimental data on bulk properties (e.g., electrical/thermal conductivities, transference numbers, electro-osmotic drag coefficients, (transport) diffusion coefficients, viscosities, heat
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embankment health through the integration of multiple monitoring technologies, enabling more frequent, scalable, and data-driven asset management. The project will investigate the integration of Axle Box
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models that combine anatomical and hemodynamic information derived from routine clinical imaging. By providing quantitative insights into coronary anatomy, blood flow, pressure, and wall shear stress
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infection with Phytophthora or Ralstonia. You will combine these phenotyping data with bacterial and fungal microbiome profiles to build predictive models of pathogen invasion and plant performance. Working
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some experience with programming and/or scientific computer software is considered a plus. This is what we offer you A temporary contract for 38 hours per week for the duration of 4 years (the initial
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deterioration. This PhD project addresses this challenge by developing a novel “Health Passport” system for railway tracks on bridges, enabling data-driven condition assessment and supporting more efficient
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preclinical therapy development. Work collaboratively across different research environments, integrating findings from zebrafish models with data from mammalian models and other experimental systems. As part
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to express the negator (‘not’) early rather than late in the utterance. You will learn to use multiple methods, including artificial language learning and EEG, collecting data from different language
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will investigate how behavioral, physiological, and cognitive data can be used to inform real-time guidance, personalize training, monitor progress, and adapt support to users' changing needs