89 finite-element-analysis Postdoctoral research jobs at University of Oxford in United Kingdom
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establish routine cell surface proteome analysis using subcellular fractionation techniques, such as density gradient centrifugation and surface biotinylation followed by enrichment, to explore the surface
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new data will be linked with information from samples previously collected during pregnancy, there will also be opportunities to be involved with analysis of multi-omic data to study mechanisms
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, fluorescent microscopy, etc.), as well as extensive experience in quantitative proteomics (both sample preparation and data analysis) is expected. As a postdoctoral researcher, you are expected be able
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consortium, the research involves elements of design, novel process and equipment development, modelling, manufacture, characterisation and data science. All applications must be made online using the Oxford
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of glycoprotein structural analysis using bottom-up mass spectrometry. The project will also include developing and applying applications in glycomics and native MS. Our goal is to characterise the structure
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correlating findings with analysis of patient material. You will take a lead role in conducting wet lab experimentation, applying state-of-the-art single-cell multiomic approaches, including transcriptomic
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the sensitivity of tumour cells to radiotherapy, with the ultimate goal of improving cure rates while minimizing side effects. A key component of our work involves translating laboratory discoveries into clinical
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analyses, including tasks and analysis using AI language models (LLMs). The postdoctoral researcher will co-lead the ethical application process for clinical fMRI and online behavioural studies and supervise
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computer programs to design experimental paradigms, analyse data and conduct advanced statistical analysis. Prior experience in running neuromodulation studies including TMS and TUS is essential. You will be
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. The work will be exclusively in-silico analysis of human rhythmic behaviour, including sleep and chronotype, and cardiometabolic disease. We will use publicly available data and apply causal inference