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data visualisation methods; training in the application of LLM-based analytical methods for both text and image). Experience, expertise and demonstrated success in delivering complex research projects
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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-economic analysis and life cycle assessment methodologies. • Proficiency with modelling and simulation software relevant to TEA and LCA. • High analytical ability to analyse and illuminate data
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the use of large administrative data to understand and address inequality. OI has published seminal work on national trends in upward mobility ; racial disparities ; the role of neighborhoods , social
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low-valent main group compounds with unique electronic structures and studying their reactivity, particularly boron-containing p-block molecules. Key Responsibilities: Research/project progress Data
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internationally recognized leader in the science of economic mobility and in the use of large administrative data to understand and address inequality. OI has published seminal work on national trends in upward
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language models (LLMs), including tasks such as data preprocessing, feature extraction, model training, and evaluation. Background in Generative AI reserach, including multi-modal LLMs. Background in AI
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of secondary particles, including atmospheric nano-particles. The successful candidate will work with Professors Zongbo Shi and other team members to analyse aerosol and gas mass spectroscopic data, carry out
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products. Apply the knowledge to correlate results / system operation. Set-up and monitor the performance of systems Job Requirements: PhD degree in a relevant Science or Engineering field Strong analytical