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hundreds of samples from multiple independent marine transmissible cancer clones. The role provides an exciting opportunity to combine single-cell cancer genomics with molecular cytogenetics and statistical
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learning architectures including generative models, particularly for sequence or structural data (e.g. transformers, graph neural networks) Proved experience in working independently and as part of a
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will be the analysis of virus sequence data generated through our surveillance activities. Surveillance will be based on next-generation sequencing of viral RNA/DNA extracted from wastewater samples. We
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contribute to the study and sequencing design, collaborate with experimental biologists to validate the hypotheses, and advise and supervise computational staff and students. You will write research articles
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the diagnosis and long-term monitoring of patients with Multiple Sclerosis (MS). This project follows a cohort of patients with MS with a dataset of measures at regular intervals including traditional clinical
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, including next generation sequencing is essential. The successful candidate will be highly motivated and enthusiastic with an outstanding academic track record, good communication skills and the ability
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advanced next-generation sequencing techniques. There is also a project management component. Importantly they will liaise with the tissue bank and surgical team to facilitate the collection and processing
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candidate will evolve drug-susceptible fungal isolates into antifungal-resistant isolates under laboratory conditions. Using whole-genome sequencing and comparative genomics, they will identify the genetic
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will be involved in processing and analysing tissue collected from patients undergoing surgery, using whole genome sequencing, transcriptomics and proteomics. You will be heavily involved in designing
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(e.g. nanopore-based sequencing, reverse genetics, immunoblotting, luciferase-based assays, RT-qPCR, microscopy) to study virus evolution and innate/adaptive immunity in the context of viral infection