275 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Simons-Foundation" positions at University of Sheffield
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colleagues and transform complex information into actionable insights that drive strategic business decisions. If you’re a proactive problem-solver, who values curiosity and a collaborative approach to move
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enforce the 5S and H&S approach to workshop cleanliness and housekeeping. You might have a Higher National Certificate in Mechanical Engineering. The ability to collect machining and manufacturing data, a
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where required. This will include holding the budget for this region and becoming a single point of contact/expert for all stakeholders based in your region. Provide information, advice, and guidance
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. Data collection and reporting, including coordinating the work of other researchers where appropriate and following up tasks to completion. Travel to study sites around the UK to undertake study quality
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information exchange. In this project, you will explore different facets of the following problems • Geometric interpretation of a distributed nonlinear controller in terms of controllability and reachability
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Traditional machine learning (ML) approaches require large volumes of annotated defect data and significant manual oversight. For the aerospace industry, this, combined with rare, but critical, defect examples
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Molecular Biology experimental techniques, such as PCR and molecular cloning and experience with analysing data from high-throughput sequencing experiments, including analytic pipelines, and the development
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. Requirements: 1st or 2:1 degree in Engineering, Physics, Mathematics, or other Relevant Discipline. For further information please contact Dr Jose Curiel-Sosa (j.curiel-sosa@sheffield.ac.uk) Funding Notes
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protocols, and analysing data, and who is motivated by translational work that is intended to function in real patients rather than remain as a laboratory demonstration. Entry requirements Candidates must
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& Castello, 2024). Applicants will also likely draw upon seminal frameworks to help make sense of the data, such as that of legitimate peripheral participation (Lave & Wenger, 1991), and upon writing on AcLits