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, neuroscience, machine learning, or related fields and/or merit/distinction-level performance in a relevant postgraduate degree (e.g. MSc) Experience of working in a neuroscience, clinical or engineering research
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The Open University Business and Law Schools are inviting applications to join our campus-based PhD Programme and our new PhD by Distance Learning Programme. The starting date for both programmes is
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marginal structural models will be extended with machine learning techniques for counterfactual prediction and to support sensitivity analyses Candidate The studentship is suited to a candidate with a strong
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and kinematic models with machine-learning-based channel state information (CSI) prediction to enable robust, low-latency connectivity across multi-layer NTN systems. This PhD project sits
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filled. This fully funded PhD explores AI-native and sensing-aware wireless systems where communications and sensing are co-designed end-to-end. You will unify modern machine learning, statistical signal
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accelerators originally designed for artificial intelligence. These accelerators achieve exceptional performance by using low precision arithmetic, which is sufficient for machine learning tasks but much too
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? This PhD project offers a unique opportunity to apply machine learning to solve a critical engineering challenge within the railway industry. The Challenge: Rail grinding is a crucial maintenance activity
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. You will focus on machine learning, but will be involved in all areas. There are also spinout opportunities. For details: PhD information sheet The team have wide experience studying bumblebee behaviour
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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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properties of representative sediment classes. · Evaluate methods for predicting sediment type and physical properties from geophysical data using machine learning. · Assess the reliability