446 web-programmer-developer-"https:"-"University-of-Cambridge"-"https:"-"https:" positions at University of Sheffield in United Kingdom
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of all polluting vehicles by 2035. With over 14 million electric cars on the road globally in 2020, the majority of the lubricants utilised for these vehicle transmissions were developed for non-electric
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Model Based Design and Flight Testing of a Vertical Take-Off Vertical Landing Rocket (C3.5-MAC-John)
Landscape Award at the University of Sheffield. This project will develop a Vertical Take-Off Vertical-Landing (VTVL) rocket, also known as a “propulsive lander” or “hopper”. The technologies developed and
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to participate in the world-leading research undertaken by the EPSRC Doctoral Landscape Award at the University of Sheffield. This project aims to develop and demonstrate novel bio-inspired micro-electromechanical
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activities, staff development, participate in the University Staff Review and Development Scheme (SRDS), and postgraduate educational activities as appropriate. An appropriate honorary clinical contract will
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to define information as a measurable quantity. This project aims to develop new information theoretic methodologies for identifying causal behaviours, embedded in data, in order to help diagnose the cause
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. This project will develop a revolutionary new type of microscope—a "quantum sensing microscope"—to observe the secret life of bacteria as they interact with the body’s defence system. This will give us a way to
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; in particular medicine and the development of new pharmaceutical compounds. This project will involve the synthesis of functionalised magnetic Nano-particles designed to bind a single target protein
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BBSRC Yorkshire Bioscience DLA Programme: The needle in the haystack - single molecule detection of extracellular vesicles in complex biological contexts
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BBSRC Yorkshire Bioscience DLA Programme: The genetic and developmental control of complex nanostructure formation in butterfly wing scales
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problems. A key aim of this PhD is therefore to develop novel IRL algorithms tailored to this setting, capable of extracting hidden reward functions from real-world, imperfect data. This will allow us to ask