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of progression to secondary acute myelogenous leukaemia (sAML). You will take a lead on developing data analysis approaches to search for targetable genetic, epigenetic, or epitranscriptomic mechanisms
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-time systems. The role will involve working with large and multi-modal datasets (e.g., images, video, audio, and sensor data), and deploying solutions in real-world environments, particularly in robotics
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of progression to secondary acute myelogenous leukaemia (sAML). You will take a lead on developing data analysis approaches to search for targetable genetic, epigenetic, or epitranscriptomic mechanisms
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together with relevant experience; have expertise and experience in survey design, quantitative research methods, and advanced statistical analysis; experience in managing large-scale data collection
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About us King’s History is an intellectual home for scholars of every region of the world, who use approaches which range from local micro-histories to large-scale quantitative analysis. We
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rhythms in population health. This post is part of a large, interdisciplinary research programme, offering attractive opportunities to work across conventional boundaries and pursue hypothesis-led science
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series, research seminars, and workshops. Candidates will possess a PhD (or be close to completion) in any relevant area of Management. The successful candidate will have expertise in composing large
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for both ligands and novel coordination clusters under a range of conditions. Candidates must also be able to work well independently but also as part of a large team, regularly reporting on progress
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experts in their fields: Dr. Muhammad Afzal (Senior Lecturer, Lead of Big Data Analytics): Dr. Afzal is an AI and data science expert with a strong research portfolio spanning AI applications in computing
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research with demonstratable experience and expertise across quantitative and qualitative data analysis. The candidate will have the ability to work with large complex data sets and communicate complex