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computer scientists to design paradigms that compare "active" learning (standard VR) against "proprioceptive" learning (haptically guided movement), measuring outcomes such as path efficiency, force
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. B1 Grundstufe (praedoc) Limited until: 31.03.2030 Reference no.: 5385 We invite you to join the Operational Quantum Information Team (Dakić Group) to work on a theoretical project on the foundations
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this challenge by developing modern data driven tools that help predict and manage corrosion in next generation bio refineries. The project brings together leading researchers from University of Leeds
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data analysis pipelines using ImageJ, R, MATLAB and relevant programming languages. Plan, troubleshoot and optimise experiments, maintain meticulous records, and prepare data, manuscripts and grant
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scientists. This PhD studentship is the foundational computational element (WP1) proposed for a major 8-year project ("The Self-Driving Microscope”). The project’s goal is to build an autonomous, AI-piloted X
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computational scientists and surgeons exploring novel ways to transform research and practice in surgical care. Please feel free to contact the main supervisor informally with your CV and a short list of
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Cranfield University is excited to invite applications for a PhD studentship focused on developing and validating innovative origami-paper eDNA sensors with community scientists for the rapid
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University Belfast, University of Manchester, University of Edinburgh and University of Bristol. BioAID will train the next generation of scientists in Artificial Intelligence and data-driven approaches
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TypeFixed-termWorking TypeHybridAvailable for SecondmentNoClosing Date30-Apr-2026JD_Param11NoJD_Param12No Two 3.5 year PhD studentships in Artificial Intelligence in Medicine, or Health Data Science, funded
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4D imaging, their high data rates limit their use in real-time applications. As a result, the available benchmark data for developing numerical models to predict transient multiphase flows is limited