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Field
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of small cryptic plasmids in the development and spread of antibiotic resistance, and ii) Use machine learning tools to examine the complex interplay between bacterial hosts, various plasmids and resistance
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Applications are invited for a position in the rapidly expanding data analytics run by Prof Adam Dubis. The main focus of the team is to develop deep learning tools for prediction of disease progression
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securing well designed and well executed analyses of food? Are you eager to take on the challenge of improving analytical techniques in this field using state-of-the-art measurement systems such as LC-(HR)MS
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the material in the facility available at Cranfield’s high temperature corrosion laboratory. A detailed analytical phase. for better understanding of the microstructure, requires working on the advanced
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technology and economics Experience in energy system modeling is beneficial First programming skills, ideally in Python Independent and analytical way of working Reliable and conscientious working style Fluent
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completed scientific university education (Master's/Diploma) in food chemistry, chemistry or a related field sound knowledge and experience in the use of instrumental analytical methods such as HPLC-MS, GC-MS
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courses. Browse all courses Take your development further with advanced learning and award pathways. Pathways to Politics for Women Public Sector Management Enterprise Leadership For organisations Achieve
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chemical evolution in the magma reservoir. The geochemical composition, isotopic tracers and the physical properties of the magmas are examined analytically and experimentally. They make it possible
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from conventional materials (e.g., traditional metals), two-dimensional materials, and their combinations. The project will employ a broad spectrum of analytical, semi-analytical, and numerical