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modifiers that selectively target cancer cells and form bioactive secondary structures. You will collaborate closely with partners across the network to develop conjugation strategies, evaluate biological
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electrolyser for CO production, and derisk for further commercialisation. The project aims to addresses the main priorities of the engineering net zero mission by accelerating deployment of a new technology that
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successful you will have: A PhD (or equivalent professional experience) in a discipline relevant to responsible AI, including computer science, AI, data science, science and technology studies, law, public
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observe how new treatments interact with a living, beating heart. This lack of real‑time visibility slows progress in regenerative medicine, particularly for therapies such as engineered heart tissue (EHT
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chronic inflammatory diseases. You will design and synthesise novel DNA constructs and chemical modifiers that selectively target cancer cells and form bioactive secondary structures. You will collaborate
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: Architect event-triggered compute stacks using industry-standard orchestration tools (e.g. Kubernetes and container workflows), and to engineer loading strategies for managing highly-irregular flows of data
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for travel and professional development. To be successful you will have completed your PhD in a relevant (or equivalent professional qualifications). You will have: a strong background in survey research, with
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will have a PhD, or be close to completing one, in a relevant discipline such as pharmacology, molecular biology, neuroscience, biochemistry, physiology or evolutionary biology. You will have experience
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organisational settings. Applicants should have a MSc degree or PhD in psychology, neuroscience, cognitive neuroscience, or a closely related discipline. Previous experience collecting and analysing EEG data is
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development of postgraduate and PhD researchers. You will have the opportunity to contribute to a programme of research that will inform decisions about how best to reduce disparities in maternity outcomes