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, statistics, data science, and public health. The goal is to develop new methods that allow researchers to learn from sensitive health data without compromising individual privacy. Using unique, nationwide
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Do you bring together domain specific knowledge from the social sciences with a genuine, hands-on command of AI and/or digital methods? Would you like to advance research that integrates state
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for using AI to develop social engineering attempts. This project combines human subject research of learning and decision making, Human-Computer Interaction, and the advancement in AI methods
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methods for causal inference using large-scale observational healthcare data. The project will address fundamental methodological challenges in estimating causal treatment effects from longitudinal
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PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (deep learning, computer vision, robotics) Number of awards: 1 Award information: Fully funded PhD studentship covering Home
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for data-efficient vision foundation models. Foundation models in computer vision currently rely on massive datasets and brute-force scaling. This leads to high data requirements, hidden biases, limited
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primary regenerative braking. EMBs are highly sensitive to EV harsh operating conditions. This project addresses this challenge by developing AI-based EMB clamping force estimators and robust control
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, engineering, mathematics, physics or related field; strong programming skills; interest in ML, computer vision, robotics, embodied AI or autonomous systems; motivation for independent research and high-quality
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NIHR Applied Research Collaboration (ARC) South West Doctoral Award: Supporting inclusive research collaboration and design through creative methods Applications are invited for a three-year PhD
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dynamic experiments of pristine and (gradually) damaged structures to collect data for the state estimation methods. Develop signal processing methods to estimate, enriched by physics-based information