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Field
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Applications are invited for a Research Fellow position on the UKRI-funded Turing AI Fellowship project ‘Event-Centric Framework for Natural Language Understanding’ led by Prof. Yulan He. The 5-year project aims
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doctoral thesis and of your master thesis, for each three pages, plus table of contents, and review and grading reports copy of the certificate of your completed doctoral and master program proof of language
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cell RNA-seq, ATAC-seq Experience with python and/or R programming languages, including single cell package ecosystems (scanpy and/or Seurat) Experience working within HPC environments Experience working
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. Proficiency in the use of statistical programming languages and analysis of large datasets and strong publication records would be essential. Previous experience in atmospheric dynamics and predictability is
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cell RNA-seq, ATAC-seq Experience with python and/or R programming languages, including single cell package ecosystems (scanpy and/or Seurat) Experience working within HPC environments Experience working
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for future research collaboration. • To plan and manage own research activity, research resources in collaboration with others and contribute to the planning of research projects. • To deliver training
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your academic experience. Relevant language skills are desirable, but not a requirement for the post. Preference may be given to candidates who have experience of working with national and international
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) Country United Kingdom Application Deadline 30 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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hepatitis and liver disease. This post is funded by the National Institute for Health and Care Research (NIHR) as part of a significant research programme that leverages large-scale healthcare datasets
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, computer science, statistics, or a related field together with strong programming skills in Python, R, or similar languages, and proficiency in high-performance computing. You will have experience in large-scale