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. Bioinformatics techniques will include database-driven analyses and quantitative comparative genomics approaches. They will be close to completion or hold a relevant PhD/DPhil, together with relevant experience
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scientists, clinicians and mathematicians will explore the mechanisms of evolved adaptive response to therapeutic selective pressures in colorectal cancer. You will develop and apply advanced bioinformatics
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We are seeking an enthusiastic and highly motivated Postdoctoral Research Associate in Microbial Bioinformatics to join the PathNoma Alliance, an international multidisciplinary research programme
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should hold, or be close to completion of, PhD/DPhil in molecular microbiology or biochemistry. You must have relevant experience in molecular bacteriology, plasmid biology and bioinformatics, specifically
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bioinformatics and spatial analysis techniques to large-scale spatial transcriptomics and imaging datasets, using tools such as MuSpAn to identify spatial biomarkers and uncover the biological mechanisms driving
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software packages; proficiency in handling large datasets including bioinformatics and biostatistics; and knowledge of complementary structural and biophysical methods. Specialist knowledge in the discipline
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regulation and/or DNA replication. Experience with genomics and next-generation sequencing. Basic bioinformatics skills. Interviews are due to be held on November 2nd - 4th 2026 This post is subject to
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quantitative proteomic data with a degree of statistical rigour using common freely available software packages; proficiency in handling large datasets including bioinformatics and biostatistics; and knowledge
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outcome sets. You will either need a PhD (or be nearing completion), in computer science, data science, artificial intelligence/machine learning (AI/ML), health data science, bioinformatics or a related
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established and emerging bioinformatics, statistical modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics