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rules which enable effective learning in large and deep networks and is consistent with biological data on learning in the cortex. In particular, the research will focus on evaluating and extending a
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). About the role The project's primary goal is to investigate how low-dose IL-2 affects the neuro-inflammatory process. You'll use advanced cellular immunology techniques to conduct deep phenotypic and
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project will likely use a combination of single particle cryoEM, cryoET, and X-ray crystallography, you should be an expert in at least one of those techniques and keen to learn the others. You also should
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state-of-the-art machine learning and deep learning techniques (such as generative adversarial networks), with empirical fieldwork in Norwegian glacier environments. As a Postdoctoral researcher, you will
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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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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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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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, 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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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