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University colleges, and discounts at University museums. See https://hr.admin.ox.ac.uk/staff-benefits Application Process Applications for this vacancy are to be made online. You will be required to upload a
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or sensor arrays. Experience generating, processing and analysing large material property datasets including correlating between multiple techniques, or developing computational reconstruction techniques
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to that data will be strictly controlled. More information relating to the manner in which we process your personal data is located within our privacy notice for staff, job applicants and others working
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strictly controlled. More information relating to the manner in which we process your personal data is located within our privacy notice for staff, job applicants and others working at the University
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) for queries related to the application process. Please quote reference NM46040 on your application and in any correspondence about this vacancy. The University actively supports equality, diversity and
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acquisition of a range of environmental and operational data in the digitisation of food manufacturing processes for processing using applied AI techniques. We anticipate the successful applicant will develop
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contact Davide Costanzo, Professor of Particle Physics: on d.costanzo@sheffield.ac.uk Next steps in the recruitment process It is anticipated that the selection process will take place before 31th March
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drive the gradual development of these technologies toward real-world applications. This involves engineering experimental hardware for cell culturing workflows, optimizing experimental processes, and
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fluid dynamics (CFD) simulations, Finite Element Analysis, manage and execute the procurement of the build, run the aerothermal testing and process and communicate the results. The skills, qualifications
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the ability to sustain themselves at unpredictable conditions - that is, to autonomously prevent faults and restore lost function, and thus allow the machine’s continuing operation. In this project we will