13 condition-monitoring-machine-learning Postdoctoral positions at University of London
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2025. We seek to recruit a Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based
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, Spain and Norway. The project runs until early 2028 and investigates the potential role of performance-based arts in understanding how coastal communities learn about and respond to ecological crises
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interest to identify cancer drivers from genomic data using machine learning (Mourikis Nature Comms 2019, Nulsen Genome Medicine 2021), study their interplay the immune microenvironment (Misetic Genome
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practice impact while also learning about machine learning techniques. The successful applicant will work in the newly formed Health Equity Evidence Centre and innovative new centre that will generate data
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populations using patient samples and employing a combination of multi-modal techniques (scRNA-seq, scATAC-seq, ResolveOME) to develop novel assays for disease monitoring. The post is based at the Barts Cancer
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possible for this role. Royal Holloway is committed to equality, diversity and inclusion (EDI), and encourages applications from all people regardless of age, disability, gender, marital status, parental
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under real-world conditions. The role includes collaboration with leading 2D materials manufacturers, offering potential for interdisciplinary research and travel. About You You should have a PhD (or be
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encourages applications from all people regardless of age, disability, gender, marital status, parental status, race, religion or belief, sexual orientation, or trans status or history. More information on our
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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
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, presentation and analytical skills and willing learn additional skills as well. Self-motivated, hardworking, flexible and professional approach to work. About the School/Department/Institute/Project The Faculty