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datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep learning architectures including generative models, particularly
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We are seeking a full-time Postdoctoral Research Assistant to join a cross disciplinary research project to improve our understanding of colorectal cancer. Deep learning has revolutionised image
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bioinformatic workflows. Familiarity with biomedical ontologies and text mining on Electronic Health Records and biomedical literature Knowledge of machine learning / deep learning with an interest in
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infrastructure. These efforts will directly enable innovative data analytical approaches, including federated and deep learning, with a focus on real-world data for rare cancers. This research will directly
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-traditional, e.g., event data) and network structures (for sensor networks). In this project, we will investigate Bayesian deep learning approaches to training models under uncertainty for several sensing
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, e.g. experience fitting Reinforcement Learning models or applying Agent Based Modelling to human behavioural data. You should have a deep understanding of the strengths and limitations
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journal publications dependent on your background discipline(s) and should hold sufficient theoretical knowledge of deep learning-based methodologies as well as working with real-world data. Informal
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successful candidate will possess skills in natural language processing and deep learning. Experience of studying the robustness and generalisability of LLM would be beneficial. This is a full time post (35
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are comfortable navigating complex HPC environments and wrangling large datasets. You have experience with modelling through state-of-the-art machine and deep-learning methods and with hands
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with deep learning libraries (e.g., PyTorch) Ability to organise and prioritise work to meet deadlines with minimal supervision Strong written and verbal communication skills, with the ability to convey