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solutions to major environmental challenges. Experience with advanced cloning systems, CRISPR tools, metagenomic mining and the use of different biofilm imaging platforms is highly desirable. There
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engineering, and biotechnology to develop disruptive solutions to major environmental challenges. Experience with advanced cloning systems, CRISPR tools, metagenomic mining and the use of different
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to improve both predictive accuracy and biological interpretability. The PhD research fellow will primarily focus on developing data mining methods such as network analysis in 3D genome regulation
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experience and proficiency in educational data mining and AI for education , with the ability to handle a large volumes of data Prior experience working with LLMs, including programming, fine-tuning
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cybersecurity, machine learning, data mining or artificial intelligence. Proven ability to conduct independent research with a strong and relevant publication record. Prior AI expertise with a strong
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relevant social science expertise. You should demonstrate: Essential Criteria: A PhD, or close to completion, in Political Science, Media and Communication, Sociology or a related social science field
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incorporating language and data mining, machine learning, as well as network analysis on existing literature and data to recommend the best in vivo vaccine research strategies. The successful
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topics would be particularly welcome: statistics, data mining, machine learning, stochastic modelling, forecasting, simulation. Applications are by letter of no more than two pages setting out why you
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, Computer Science, Data Science, or a related discipline. Demonstrated expertise in sentiment analysis, opinion mining, or computational analysis of media and public discourse. Candidates should be able
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genetics/genomics, bioinformatics, machine learning, data mining, and computational programming, including software or package development. The ideal candidate will hold a PhD in bioinformatics or