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of seed gene networks”. This project aims to use reverse genetics, cross-species complementation and single cell next-generation sequencing approaches to investigate how the gene networks that regulate
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remission as a model of flare vs remission with a 50% relapse rate. Initial data analysis has taken place using the 10x Chromium single cell sequencing identifying putative cellular subpopulations
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include working with the energy systems modelling teams to explore how the social analysis can align with systems modelling to develop evidence-based pathways that inform implementation and policy. The role
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, will study the drivers of relapse in acute myeloid leukaemia (AML) with the goal of improving treatment options in this poor outcome cancer. You will perform and analyse next-generation sequencing
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Robotics and AI Fellowship (1 position available) Strategically aligned with our EPSRC-funded Doctoral Programmes (AgriFoRwArdS Centre for Doctoral Training and Doctoral Training Partnership). Research Areas
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Council, will study the drivers of relapse in acute myeloid leukaemia (AML) with the goal of improving treatment options in this poor outcome cancer. You will perform and analyse next-generation sequencing
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with sequencing bacteria in the laboratory. Key attributes of the successful applicant include: Experience with REDCap: setting up databases Experience of working in a healthcare setting, medical research
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, the development and fine-tuning of vision foundation models, multiple instance learning, survival analysis, and interpretable model development. You will also lead efforts in building multimodal deep learning
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with sequencing bacteria in the laboratory. Key attributes of the successful applicant include: Experience with REDCap: setting up databases Experience of working in a healthcare setting, medical research
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-recapture for demography and social network structure; genome re-sequencing for pedigree information and genomic prediction; diagnostic testing for infection status and prevalence of bTB. The Research Fellow