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; Midlands Graduate School Doctoral Training Partnership | Nottingham, England | United Kingdom | 3 months ago
the consumption journey. This exciting PhD Programme will look to address these challenges by employing a novel combination of data-donation, data-enhancement, and data-augmented laboratory experiments. The project
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This research project is to understand how machine learning can be exploited in the areas of target detection and tracking. Develop tracking expertise in a new student who can subsequently work
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of Computational Solid Dynamics Building upon very recent work made by the supervisory team, this FULLY FUNDED 4-year PhD project will investigate challenging aspects such as: (1) exploration of a truly “n” multi
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eye tracking, we will study how people coordinate and interact within these settings. The project is carried out in collaboration with partners at RWTH Aachen University and the University of Rennes
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associated threats. The research project of the PhD student will thus focus on defining methods to track, monitor, and manage the use of GenAI. While this can rely on recentely proposed telemetry framework
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) for different scientific applications, including simulations, large-scale data analyses and AI. This will involve designing test protocols, building test benches to track power and energy usage, and running
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We are seeking an enthusiastic and capable individual to join our team as a PhD researcher in developing instrumentation and simulations to monitor and track satellites. The successful candidate
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with an excellent GPA or a proven track-record of relevant research will be considered for an interview. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and the
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PhD Scholarship in History Job No.: 678754 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term appointment Remuneration: The successful applicant will receive a
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Lead Supervisor name: Andrew Callaway, email: acallaway@bournemouth.ac.uk Project description: This PhD programme will determine the most clinically acceptable methods for emergency response teams