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rare moment to reshape how we learn from health data. Your journey will blend AI, and engineering creativity with ethical responsibility. You will experiment on large, real-world collections of de
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an important part of this role. You will be expected to assist and lead fault finding for complex technical issues which occur on a large university campus with a varied building stock. A working technical
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year round Details Proteins bind and recognise each other using large surface areas. This recognition process is vital for a variety of biological applications. Sensing and recognizing specific proteins
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and produce management information to enable rapid decision making on project priorities and resources, and to allocate tasks across the wider research team. You will be an active member of the research
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firefighting search and rescue teams. The project scope is on real-time solutions for a small, medium and large number of entities with a swarm of UAVs. Computer Vision and Machine Learning approaches will be
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detectors at the CERN Large Hadron Collider. You will work alongside and receive training from researchers and research software engineers within STFC, RSE Sheffield and with international partners (e.g. Oak
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of Sheffield. The role is part of a programme of research that is fully funded by the Aerospace Technology Institute (ATI) in a large collaborative programme with several Industry partners, including Airbus
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digital capabilities, they will be able to build relationships with, and between, academics and businesses (from SMEs to large multinationals), identifying their needs to agree projects for delivering
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data gaps by combining process simulation (e.g., Aspen software) with machine learning techniques. By developing accurate, large-scale life cycle inventory data using enhanced digital tools like deep
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effectively and efficiently within both small and large teams Essential Interview Experience of performing experimental work Desirable Application/Interview Further Information Grade 7 Salary £38,784 – £47,389