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nerve cord). The principal focus will be the development of open source tools for the analysis of connectomics data. This will include developing tools to improve the quality of neuron identification and
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application of comprehensive polar metabolite analysis methods. Scientists are encouraged to apply if they have substantial practical experience in the development of comprehensive quantitative methods
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interactions but is frequently underexplored by synthetic chemist. We have used this extensively in the context of transition metal catalysis (perspective: J. Am. Chem. Soc., 2022, 144, 18195, review: Chem. Rev
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, catalysis, or a related field, and a strong background in transition metal catalysis. Experience in reaction kinetics, mechanistic studies, and process optimisation would be highly desirable. This is an
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cloning, synthetic biology, systems biology, computational modelling, and image analysis would also be valuable to the role. The successful applicant will be an excellent team player, highly solution
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of different cohorts. The primary role of the post holder will be to lead projects involving the quantitative analysis and interpretation of genomic, multi-omic and phenotypic data using polygenic scores, GWAS
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/ ). Your tasks will include data collection, analysis, write-up, and dissemination of ongoing and future research. Furthermore, you will play a crucial role in supporting and training PhD students and other
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the scientific analyses of glass, including compositional analysis using techniques such as SEM-EDS and LA-ICP-MS, an ability to thrive as part of a diverse team and a willingness to contribute
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stable cell line generation). ¿ Experience in molecular biology techniques: cloning, PCR, mutagenesis, western blotting, immunofluorescence, DNA and RNA isolation and protein analysis. ¿ Experience in
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of linguistic representation decodable from neural activity. Applicants should hold a PhD (or equivalent) in cognitive neuroscience or related field and have strong analysis skills using python and machine