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. This is a highly collaborative project, and it will involve working closely with other post-doctoral researchers and academics from the Universities of Edinburgh and Oxford. You will lead the bioinformatic
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microbiological culturing, molecular skills, bioinformatics and statistics. The project is flexible and can be guided by the interests of the student. Please apply for this project using this link: https
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statement when you apply. Criteria Essential or desirable Stage(s) assessed at PhD (or equivalent experience) in a relevant subject area such as molecular biology, cell biology, cancer biology, bioinformatics
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reveal hidden patterns. The project aims to apply and adapt TDA techniques from various fields—such as physics, mathematics, bioinformatics, and neuroscience—to uncover new insights and improve ML models
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cutting-edge approaches: 1. Population Genomics: You will utilize whole-genome sequencing and bioinformatic analysis to: * Characterize the genetic diversity and evolutionary relationships within a
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assembly and pan-genomics -Small RNA and methylome analysis -Molecular biology and functional genetics -Bioinformatic analysis of large datasets The student will join a vibrant, highly collaborative, and
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lab https://sites.google.com/sheffield.ac.uk/lahirilab/) with structural bioinformatics (Chaudhuri lab, https://www.sheffield.ac.uk/biosciences/people/academic-staff/roy-chaudhuri) and plant genetics
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-read sequencing and SNP detection. The student will join a vibrant microbiology group in Sheffield and receive a broad training in molecular and microbiology as well as imaging and bioinformatics
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genetic diversity. Projects could involve field work, experimental work, laboratory work and/or bioinformatic analysis of genomic data. You would receive training in the relevant techniques, as
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/experiments. performing studies on chick embryos, investigating the role of axial mesendoderm on hypothalamic development. Perform bioinformatic analyses, including data mining of chick scRNA-seq datasets