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in a highly interdisciplinary project funded by the European Research Council (ERC). The overall aim of the project is to understand how intercellular signalling in developing embryos allows them
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evolution. Where Covid-19 has resulted in substantial disruption to your work or research outputs, please explain this by providing an additional paragraph in your supporting statement. The University
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. Ready to be part of our team? Let’s shape the future together! About the team: Our group develops and applies quantum mechanics-based methods for the description of condensed matter systems, including
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range of disciplines, funded by the Leverhulme Trust to increase knowledge of how the relationship between humanity and the natural world is changing, and how we might maintain and develop a sustainable
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scientific publications, patents, and seeing collaborators translate our work into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and
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research, adapting existing and developing new scientific techniques and experimental protocols. You will work with limited supervision to design and accurately execute experiments to achieve the goals
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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precancers and developing targeted interventions, including vaccines, to intercept them. The project focuses on designing, validating, and preclinically testing neoepitope-based mRNA vaccines to prevent BRCA
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of Engineering, to work on an EPSRC funded project – ‘Engineering Twist'. The project aim is to develop experimental approaches to characterise enriched continuum models for mechanical metamaterials, and their
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through long-term impact assessment and optimization. The goal is to develop a framework to estimate carbon emissions across AI's development, operation, and use. This framework enables stakeholders