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Field
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bioinformatics. The Department's research strengths currently lie in behaviour and neuroscience, conservation science, ecology and all aspects of evolutionary biology. How to apply for sponsorship Please address
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population genetics, bioinformatics, computational biology, statistics or probabilistic machine learning and computer science. Experience of working with large genotyping or sequencing data sets A proven
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these two processes. The postholder will exploit a series of single-cell and spatial transcriptomics datasets of glioblastoma initiation and recurrence generated by the team to dissect the cell-intrinsic and
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including next-generation sequencing, bioinformatic analysis (R and/or python), mammalian cell culture. The post holder will be comfortable working both independently and in a collaborative environment. What
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bioinformatics. The successful candidate will join a team with a strong track record in developing computational tools and informatics infrastructure for metabolomics applications in toxicology, systems biology
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including next-generation sequencing, bioinformatic analysis (R and/or python), mammalian cell culture. The post holder will be comfortable working both independently and in a collaborative environment. What
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experimentation and thermodynamics calculations. Establish a high-throughput bulk materials processing route to enable efficient characterisation and parallel testing of multiple compositions. Develop a high
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bioinformatics analysis and Drosophila work would be desirable but not necessary. This position will be supervised by Prof Hansong Ma in the School of Biosciences at the University of Birmingham. Main Duties
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foundation in fundamental biofilm research, microbial community assembly and manipulation, and biofilm reactor operation is essential. Experience in metabolic engineering is desirable. The successful candidate
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experience: Essential criteria PhD awarded in genetic epidemiology, statistical genetics, bioinformatics or related discipline Postdoctoral research experience in genetic epidemiology, statistical genetics