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of machine learning for healthcare and related topics Deep knowledge of multi-modal learning, transfer learning, foundation models, and self-supervised learning. Experience in dealing with large
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electronic health records (EHRs) from multiple UK hospital centres using advanced data analytics including machine learning, deep learning, and statistical techniques—with a particular emphasis on deep
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of biosystems and for extracting knowledge from (vast) sets of biotech data. A core technology leveraged by researchers at the center is deep machine learning, targeting the development of innovative tools and
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expertise in analysing/ training models on biological or chemical datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep
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on “Maternal Immune Activation” involving the development of novel artificial intelligence methods (graph and geometric deep learning, LLMs, …) working on methods for predictive multi-omics integration
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will disrupt today’s most vibrant research frontiers: Embed model-based AI into self-supervised pre-training pipelines Finetune multimodal deep learning models that answer diagnostic questions about X
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) Doctoral Degree (or foreign equivalent) in hand by September 1, 2025. Deep knowledge of functional materials and
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Qualifications: PhD in experimental particle physics at the time of appointment. Preferred: Deep understanding of the particle detectors, particle identification, data analysis Machine learning experience is a
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to implement advanced computational pipelines, including machine learning, deep learning, Bayesian inference, and probabilistic mixed membership modeling for innovative research. · Contribute
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own surveys and secondary data collected by third parties. The ideal candidate for the position will be a recent PhD graduate with a deep interest in this domain who can provide research support in