149 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"UCL" positions at University of Manchester
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applications from all sections of the community. This role will be based within the Research Development and Innovation team in the Faculty of Science and Engineering. The team consists of the Faculty’s
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transcriptomic organisation, using high-resolution single-cell and spatial transcriptomic data. The successful candidate will develop computational frameworks to integrate and analyse multi-modal datasets
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child health. The successful candidate will contribute to the development of advanced mathematical and computational models to analyse high-dimensional multi-omic datasets, including genomics
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clinical practice globally. You will develop/expand your skill base in data acquisition, management and security and have the potential to conduct studies related to key clinical outcomes of interest. Key
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, continuous challenge by exposome factors can promote development of chronic inflammatory diseases (CIDs) within this tissue, as well as systemically. Thus, defining the cellular networks that underpin
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adversely affecting their infection prevention credentials. This involves applying advanced materials science and engineering principles to develop and implement innovative recycling and consider
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of working in the laboratory environment. The post holder will be responsible for processing and analysing clinical samples (tumour biopsies, blood, stool and urine), developing state-of-the-art techniques
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cutting-edge machine learning methods for spatial omics and for multi-modal data integration. The post-holder will also collaborate on the development of new computational methods to support the CoRE’s
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development of a computational pipeline that integrates multi-omic data at the cellular level across exposomes and diseases, revealing novel biology and shared mechanisms of immune regulation. You will be
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Officers with the planning and delivery of training and the development of support resources, and thus contribute to the delivery of high quality and effective online and blended learning within the Faculty