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computational analyses of epigenomic/transcriptomic data and machine learning. Experience in single-cell omics data is desirable. The post holder will be responsible to develop pipelines for the analysis
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-edge machine learning techniques will be used, including Large Language Models (LLMs). About Queen Mary At Queen Mary University of London, we believe that a diversity of ideas helps us achieve the
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” which examines signal processing and machine learning methods for inferring active travel activities from optical fibre signals. About You Applicants must have an Undergraduate Degree in Computer Science
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical
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the areas: AI, deep neural networks, machine learning, applied topology, probability, statistics, signal processing. About the School The School has an exceptionally strong research presence across
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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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, 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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ambitious who has obtained their PhD, has a strong portfolio of design practice and has begun an academic career in health research. The post holder will provide guidance to junior members of the research
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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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at the forefront of contemporary trauma care. About You The post holder must be pursuing / completed a PhD degree or equivalent in Bio Medical Science related field. Pursuing / completed PhD degree or equivalent in