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in regular team meetings and contribute to data analysis discussions. Work can be completed remotely/hybrid Qualifications Enrollment in a PhD program in education, social sciences, or a related field
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barrier—is disrupted in these conditions, how such dysfunction impairs drug delivery, and whether restoring vascular integrity can improve outcomes. This research is part of an NHMRC-funded Investigator
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With its work, the Leibniz Institute of Vegetable and Ornamental Crops (IGZ) contributes to a better understanding of plant systems and thus to the development of sustainable and resilient
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Organisation Job description Project and job description Our project will make use sensing technologies (hyperspectral cameras, NIR and Raman sensors), and an edge-compute AI pipeline to sort used
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on a flat-belt conveyor and are dynamically grasped, unfolded, and oriented by multi-axis manipulators fitted with custom force-feedback grippers, and will work in close concert with a parallel sensing
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understanding of device function. The project will involve advancement and application of spectroscopic techniques and simulation tools for the measurement and analysis of the properties of spins and their role
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technical work packages: WP1 Annoyance from wind turbines WP2 Wind turbine noise data collection and analysis WP3 Wind turbine noise source modeling WP4 Wind turbine noise propagation modeling WP5 Wind farm
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Research Office Location: Newport, Shropshire TF10 8NB Salary: As per advert Post Type: Full Time Contract Type: Fixed Term - 36 months funded Closing Date: 23.59 hours BST on Monday 18 August
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Description With its work, the Leibniz Institute of Vegetable and Ornamental Crops (IGZ) contributes to a better understanding of plant systems and thus to the development of sustainable and
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PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo