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Field
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learning approaches to process and interpret large and complex Remote Sensing datasets. When joining our group, you will also join the wider and growing ecosystem of WUR , where artificial intelligence is
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analyse clinical, physiological, and patient-reported outcome data. Conduct interviews, surveys, and observational studies with patients and healthcare professionals. Translate research findings
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models; Translating research findings into both academic publications and accessible, practice-oriented outputs for policymakers and other urban partners; Actively contributing to knowledge exchange and co
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theoretical challenges motivated by astrodynamics, optimisation, control, scientific machine learning, mission design and autonomous systems, translating these into new research directions in deep learning
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Are you interested in the empirical foundations of flood damage modelling and keen to translate that knowledge into practical strategies for insurers to reduce losses through early warning and
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translate our knowledge and insights into solutions to societal issues, contributing to a sustainable society and to the development of prosperity and well-being. That is what unites us in pioneering research
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output. Carry out participant observations and walk-along-interviews with frontline workers. Publish in academic journals and translate findings into fact sheets for practitioners. Present results
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consortium This position is an opportunity to work at the interface of rigorous computational mechanics, mechanobiology, machine learning, and translational cardiovascular modeling. We are looking for a
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, or comparable industry-standard EDA tools. You have experience with system-level modelling using MATLAB/Simulink, Verilog-A or comparable tools. You enjoy collaborating across disciplines and translating sensor
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using onboard IMU signals Run a pilot home-testing study on continuous gait monitoring, assessing feasibility for future large-scale use You will translate this into a research plan aimed at peer-reviewed