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the project will focus on developing a thermal water splitting process based on complex transition metal oxides, and then studying the kinetics of the process to facilitate the design of a reactor to integrate
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the DR Amiya Bhatia. This role includes research assistant work such as handling and analysis of quantitative and mixed-methods data from pre-post and retrospective surveys, development of study
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nanotubes, enables the exploration of thermodynamic processes at the nanoscale. Carbon nanotubes serve as exceptional nanomechanical resonators due to their low mass, high stiffness, and quality factor
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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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prioritise a varied workload, meet tight deadlines and maintain performance under pressure, without close supervision. Attention to detail and a methodical approach to work are crucial. You should have strong
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a postgraduate qualification with a significant computer science/bioinformatics component, or a degree and professional experience of large-scale IT enterprise solutions. You will be able
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. Stata, R, SAS), experience in statistical analysis of medical data and a good understanding of statistical methods such as regression and GLMs. In return we offer an excellent benefits package including
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crucial in assisting the team to adapt to these new working methods. In collaboration with the Team Leader, you will develop roadmaps and vision boards, manage backlogs, and plan for long-term work
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods