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-based fiber materials. Qualification We are looking for a candidate with the following qualifications: Master in Polymer Chemistry, Polymer Physics, Material Science/ Engineering Experience with bio-based
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of pharmaceuticals using linked data from population-wide Norwegian health registries, in addition to data simulations (e.g. based in mathematical models for infectious diseases). A main focus of the project will be
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the highest two categories in REF2021 (world-leading or internationally excellent). What you’ll need A high-quality undergraduate (ideally first class) or masters (ideally distinction) degree in a relevant
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for changes to your work duties after employment. Required selection criteria You must have a relevant Master's degree in Industrial Engineering, Logistics Engineering, Production Management, Supply Chain
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degree with either the UTS Sydney or the University of Groningen. Teaching language English Languages Our primary language in the PhD programme is English. In addition to the mandatory English language
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the main supervisor; Dr Ali Ehsan - ali.ehsan@manchester.ac.uk . Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your
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. To apply, please contact the main supervisor, Dr Thomas McDonald - thomas.mcdonald@manchester.ac.uk . Please include details of your current level of study, academic background and any relevant experience
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Classification Title: Research Assistant Professor Classification Minimum Requirements: PhD in biochemistry, molecular biology, electrophysiology, physiology, or a closely related field. Job Description: Key laboratory projects Identify protein alterations that drive radiation dermatitis and...
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to understand variability in drug toxicity, drug metabolism and drug transport. Examples of this include cell-based models such as induced-pluripotent stem cells, primary human hepatocytes and clinical studies
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Materials, mastering scientific machine learning, uncertainty quantification, and high-performance computing. Your models will inform fusion design and advance AI-for-materials. Perfect for physics, maths