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for one to two PhD students in analytical chemistry to develop analytical methods for single cell analysis and mass spectrometry imaging using direct infusion mass spectrometry. The PhD candidate will work
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methods for single cell analysis and mass spectrometry imaging using direct infusion mass spectrometry. The PhD candidate will work with and develop custom made techniques coupled to high resolving mass
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research. The student will gain valuable insight into AQP folding and trafficking mechanisms using a range of techniques. Lipidomic analysis will provide understanding of how the membrane environment
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for data analysis. The studentship covers fees at the Home rate only. How To Apply You must apply through the University’s Apply to Newcastle Portal via the above 'Apply' button. In the ‘Course choice’ tab
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systems design in Germany and Europe Active participation in scientific and public discourse (including publishing in peer-reviewed scientific journals) Your Profile: A completed Master`s degree in
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conditions chemical analysis of plant secondary metabolites using HPLC-MS and GC-MS protein isolation and characterization using LC-MS plant physiological measurements molecular biological investigations (e.g
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conditions chemical analysis of plant secondary metabolites using HPLC-MS and GC-MS protein isolation and characterization using LC-MS plant physiological measurements molecular biological investigations (e.g
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | about 9 hours ago
analysis. Objective The goal of this PhD is to formally verify the memory safety of Linux kernel drivers. The project will focus on driver interactions with the kernel, including the direct use of kernel
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; radiopharmaceutical dosimetry with novel agents and/or software techniques; alpha particle RPT radiation biology modeling and analysis of clinical trial data. For additional information on a subset of expected
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combine engineering design principles with stake-holder engagement tools to support decision-making under uncertainty. Using methods like agent-based modelling, quantitative resilience and risk analysis