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collaboration that has mapped emotional hotspots in four cities in the UK and EU using spatial analysis of social media data. The next phase of the project aims to incorporate explainable AI (XAI) to interpret
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Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing techniques to enable large-scale data search
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science methods, ideally to environmental health data, and conducting systematic reviews and meta-analysis. Further particulars are included in the job description. The post is full-time 35 hours per week
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artificial intelligence methodologies. The successful candidate will work at the forefront of computational biology, developing novel approaches for large-scale genomic data analysis and contributing
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extractions). The candidate ideally should be familiar with live tissue slicing and working with hIPSC cultures. Additionally, a major component of this post will also involve data analysis and interpretation
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science methods, ideally to environmental health data, and conducting systematic reviews and meta-analysis. Further particulars are included in the job description. The post is full-time 35 hours per week
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Drakeley and Dr Julius Hafalla, primarily focused on immunoepidemiology, as needed. The post holder will be responsible for the generation and curation of laboratory and epidemiological data from different
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part of a broader collaborative team, under the supervision of Dr Shivani Pasricha, you'll utilise advanced molecular genetic technologies like CRISPR and data analytics to understand infection dynamics
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are also open to discussing flexible working arrangements. Are you an ambitious and talented statistician with expertise in individual participant data meta-analysis (IPDMA) of clinical trials and
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route but first-time applicants might need to qualify for salary concessions. For more information, please visit the Government’s Skilled Worker visa page . For research and academic posts, we will