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- KINGS COLLEGE LONDON
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Field
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computational biologist who is looking to make high-impact contributions on exciting challenges at the scientific frontier of genome-editing. The Kellogg lab uses cutting edge genetics, cryo-electron microscopy
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of Organismic and Evolutionary Biology, which is a vibrant community of cross-disciplinary biological scientists at Harvard University. Basic Qualifications A Ph.D. degree in Bioinformatics, Computational Biology
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structural biology. Determining its impact on bacterial physiology under different environmental conditions. Investigating the evolutionary conservation and diversity of this mechanism in other bacterial taxa
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keen interest in genome biology, evolutionary biology, crop domestication history and bioinformatics. The ‘Cereal Genetics and Genomics’ group leverages technological innovations in genomics and
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the mechanistic and evolutionary drivers of patterns and processes from gene regulation to the structure and function of ecosystems and the impact of communities on the biogeochemical cycles and their adaptive
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better understand the mechanistic and evolutionary drivers of patterns and processes from gene regulation to the structure and function of ecosystems and the impact of communities on the biogeochemical
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our dynamic team. Our research program aims to advance the molecular understanding of pathogenic Escherichia coli and other emerging or reemerging bacterial and viral pathogens, with the overarching
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of rail with wider city and regional transport networks. A focus of this work is the application of optimisation techniques (e.g. evolutionary algorithms, or Bayesian techniques) to identify high performing
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application! We are now looking for Computational Research Assistants in Tumour Evolution and Single-cell Genomics. The position Cancer evolves over time and space, with subclones often acquiring new mutations
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computational models to map co-expression networks and predict systemic disease transitions. Characterise intestinal microbiome changes and their correlation with inflammatory diseases. Computational modelling