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engineering, machine learning, molecular design, and sustainability, helping to create smarter ways of identifying promising sorbents for electrochemical CO2 capture. Over the course of the project
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https://www.science.org/doi/10.1126/sciadv.adr1758 Highly motivated students from Physics, Chemistry or Materials Science Departments are strongly encouraged to apply for this post. The candidate should
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requirements and focusing on data-value maximisation. This project will utilise innovative machine learning methods and tools from process systems engineering to simultaneously optimise product quality and the
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2.1 Honours BSc degree, ideally and MSc with genetics, epidemiology or laboratory experience or an MD/medical degree or MBBS. Location: UCL Queen Square Institute of Neurology and the National Hospital
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potentially druggable targets. Depending on interest, the student will have an opportunity to contribute to other projects within the team and learn a range of important techniques such as cellular, animal