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which there exists extensive experience in the areas of machine learning, biostatistics, and medicine: Dr Yanda Meng and Dr Tianjin Huang (Machine Learning), Prof Yalin Zheng (AI in Healthcare), A/Prof
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Recently, many councils in Wales started using single transferable vote (STV) method for counting ballots. While counting plaintext ballots using STV method is straight forward, but a rank-based ballot may leak the voter’s preferences if published publicly in plaintext, as the ranking order can...
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transcriptomics and histone mark profiling as well as by live imaging approaches. As part of this project, you will have the opportunity to gain computational data analysis skills. This studentship comes with
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computational and machine learning approaches to integrate Oxford Nanopore (ONT) long-read data with bulk and single-cell RNA-seq profiles. The aim is to identify host-microbiome molecular signatures that drive
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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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represent the research group at external seminars and conferences. To be considered, you must hold a PhD/DPhil in statistical genetics, quantitative genetics, bioinformatics, computer science, statistics
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Fees for 4 years (Full time), £12,000 stipend for 3 years We are pleased to invite applications for a funded PhD studentship exploring how a curated Arts Public Programme can address pressing issues
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EPSRC iCASE PhD studentship with SLB - Computational modelling of advanced geothermal systems School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded UK Students
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are invited for a three-year PhD studentship The studentship will start on1st Jan 2026 Project Description Surgical resection is the primary treatment for meningiomas, but radiotherapy (RT) is commonly used as
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Location: UK Other Applications are invited to undertake a PhD programme, in partnership with Airbus, to address key challenges in ensuring adoption of sustainable approaches to fuel additives