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Experience with RNAseq or microbiome data analysis Basic knowledge of R programming, bioinformatics or machine learning Attributes and Behaviour Independent and team-based working ability Enthusiasm
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with spatial biology or immunohistochemistry Experience with RNAseq or microbiome data analysis Basic knowledge of R programming, bioinformatics or machine learning Attributes and Behaviour Independent
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stakeholders Knowledge of new and emerging digital tools and their application within urban planning and design (for example, the growing use of AI/Machine Learning in local planning authorities) Lecturer Grade
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of disseminating research to both academic and industrial audiences. Qualifications PhD (or close to completion) in Computer Science, AI, Data Science, Machine Learning, Edge Computing, Signal Processing
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-grained simulations, advanced sampling, and machine learning for predicting and analysing short-lived protein conformations. Enhance and automate workflows for reproducible simulations and structure-based
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one of the following analysis techniques (multiple preferred): normative modelling, dimensionality reduction techniques, machine learning, deep-learning, state space modelling, advanced statistics