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teaching interests that would further strengthen an application include machine learning, computational economics, or data-intensive methods, particularly where these areas complement macroeconomic analysis
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to capture the spatial complexity of tumor organization and its relationship to treatment response. This PhD project aims to develop robust multimodal predictive models of platinum resistance using a large
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Caribbean populations of African descent. Most mechanistic insights derive from non-representative cohorts, limiting biomarker discovery and therapeutic precision. Recent multi-omic and machine learning
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architectures. This includes among other: (a) design and implementation of machine learning and GenAI models, (b) efficient training and inference on GPU-based systems, (c) fine-tuning and optimization of large
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representatives o carrying out data analysis and report writing. Candidates will have (or be working towards) a postgraduate degree (ideally PhD) in any of the sectors: Data Science / AI Machine Learning
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Low maintenance reliable main bearings for large wind turbines Offshore Wind CDT PhD Research Project Directly Funded UK Students Prof R Dwyer-Joyce, Dr Thawhid Khan, Mr Wooyong Song, Dr Siren
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of areas, including AI and machine learning, cloud and mobile computing, computer system and information security, evolutionary computation, computer vision and graphics, and bioinformatics
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development. Demonstrated experience developing applications interfacing with machine learning libraries like PyTorch or ONNX. Demonstrated experience working with large-scale data processing and deployment
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, LangChain, HuggingFace, axolotl. Knowledge of and ability to select, adapt, and effectively use large AI foundational models. Professional experience developing solutions using NLP, computer vision, or
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and computational physics High-energy physics/astrophysics/cosmology Statistical mechanics/complex systems/non-linear physics Machine learning/first-principles calculations/large-scale simulations