88 finite-element-analysis Postdoctoral positions at University of Oxford in United Kingdom
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), based at the Centre for Human Genetics, University of Oxford. The post aims to assist with the preparation and molecular characterisation of tumours using multi-omic analysis focusing principally
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science, with applications to public and veterinary health, therapeutic development, and pandemic preparedness. You will contribute to method development, data analysis, and collaborative projects, and will
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products (e.g. transcripts and proteins) and imaging analysis. The roles of relevant parasite genes and pathways are investigated using gene expression perturbation approaches, such as RNA interference and
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supported-lipid bilayers and performing Total Internal Reflection Fluorescence (TIRF) microscopy, together with advanced skills in quantitative image analysis. You will have experience isolating T lymphocytes
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background in Linguistics, and be willing to work in a Linguistically oriented environment. The post holder must have experience with EEG and should be able to carry out EEG acquisition and analysis of EEG
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: (1) electrophysiology; (2) optical monitoring/manipulation of cell activity/neuromodulators/neurotransmitters; (3) techniques for quantifying animal behaviour; (4) data analysis, including machine
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optimising the performance of the vertex detector design for LHCb Upgrade II. Physics analysis is possible, if time allows. Applicants should hold, or be close to completing, a doctoral degree in experimental
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of expression/distribution; • Analysis of response at the level of myocardium (scar and cellular characteristics) are met. Applications for this vacancy are to be made online via the Oxford
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. The research is primarily translational in nature, involving both preclinical models and human sample analysis from clinical trials, and is carried out in close collaboration with the pharmaceutical industry
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genome/protein analysis pipelines for Mycobacteria genomics and drug target identification. Bioinformatics techniques will include database-driven analyses, quantitative comparative genomics approaches