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learning, transfer learning, foundation models, and self-supervised learning. Experience in dealing with large medical datasets (e.g., electronic health records data or medical images) Ability to use high
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learning. The post-holder will be familiar with the use of these techniques and experience of dataset construction and data mining will be essential. The successful applicant will have completed an MPhil/PhD
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Data of Job Applicants and University Personnel to learn how your demographic data are protected, when the data may be used, and your rights. Disability Services To request disability accommodation in
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, such as R, Python, or Machine Learning, to identify patterns in biological factors, disease and mortality; co-supervising and mentoring PhD candidates, MSc and BSc students; collaborating with national and
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. The research will bridge both established and emerging technical expertise within the section, encompassing areas such as FPGA and neuromorphic computing, Edge AI, machine learning, power electronics, and self
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motivated Neuroscience postdoctoral fellow. In addition to neuroscience research experience, having familiar with machine learning/AI/ big data processing will be an asset. A major part of this PDF
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experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical and machine learning methods in the context of biological systems Experience with programming (e.g
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amenable to therapeutic targeting. This position will involve the application of advanced data science approaches to explore large-scale clinical datasets extracted from electronic health records, with
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qualifications include: Experience with radio interferometric observing, data processing, and imaging. Experience with modern machine learning / deep learning techniques and software packages. Experience with time
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responsibilities Design, implement and benchmark deep machine learning models for large-scale cancer datasets that include genomics, transcriptomics, epigenomics and imaging data Collaborate closely with