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Field
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CAS will provide the necessary expertise in the analysis of complex data, including multimodal neuroimaging measurements, the use of information theory, nonlinear dynamic systems, network theory
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the biology of lung tumour evolution based around analysis of next generation sequence (NGS) data and the tumour microenvironment from the TRACERx longitudinal lung cancer program. Our aim is to trace
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, including panel regression, analysis of large administrative data, survey data, and statistical programming in Stata/R/etc; excellent oral and written communication skills in English; a commitment to academic
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dysfunction and its impact on neuronal networks, building on the complementary expertise of a team with a strong publication record in reputable journals and proven experience in identifying nervous system
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in techno-economic analysis and Net Present Value (NPV) modeling. · Experience or interest in large-scale energy demand analysis, infrastructure planning, or site selection (e.g., data centers
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methods. It may also include quantitative data analysis. The post-holder will take a role in all stages of this process, from conceptualisation to data collection and analysis, as well as writing up and
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enrichment (GO, KEGG), network analysis, genome assembly and binning, systems biology, and multi-omics integration. Apply statistical modelling, machine learning, and deep learning approaches for biomarker
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language processing and other AI methods in health and life sciences datasets Expertise in advanced computational methods such as network analysis, graph databases and structured and unstructured data mining tools
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and disease early warning. The postdoc will perform directed research to achieve the objectives of the project, specifically: (i) deploy network analysis methods to genomic co-expression data (70%), and
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and international funding bodies. Build Networks and Collaborations: Engage with internal colleagues and external partners (academic and industry) to exchange ideas, explore opportunities