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. They must work as part of a team, be willing to learn new methods and skills and persevere in case of discouraging results. The role will also include protocol development. The postholder is expected to be
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, materials and electrochemical testing methods and characterisations. Attend Faculty, Department and Programme meetings/boards as appropriate and proactively contribute to decision making. The project will
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Trust Career Development award funded research programme “Unlocking the RNA Helicase Code: From Structural Insights to Therapeutic Strategies” led by Dr. Jagtap. The overall project builds upon our novel
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. They will also help coordinate and implement future field campaigns to fill key field data gaps. Additionally, the successful candidate will be responsible for advancing cutting-edge methods for quantifying
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research into planet formation/protoplanetary discs or the ISM/star formation and may also have some experience in statistical methods and/or machine learning. Dr Winter and QMUL are committed to improving
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Kong Polytechnic University (HKPU), funded by Hong Kong’s InnoHK programme. Together, we are exploring how artificial intelligence and design can tackle some of the most pressing challenges of the 21st
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of this position within the team is the experimental work on decontamination of porous materials, although it is also expected that the successful candidate will contribute strongly to the analytical and numerical
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of support for health and wellbeing including discounted membership for our state of the art sport and gym facilities and access to a 24-7 Employee Assistance Programme. • On site nursery is available plus
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related to gravitational wave astronomy. The primary aim will be the development of advanced approaches for computational Bayesian Inference to measure the properties of Compact Binary Coalescence signals
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responsible for the development and implementation of a case study in a US or European city (to be confirmed), using ethnographic and qualitative case study methods under a cross-cultural research design