458 algorithm-development-"LIST"-"Washington-University-in-St" positions at University of Sheffield
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of projects for Cohort 2 (starting in October 2025). However, we are continuing to take applications for the remaining projects. We are now accepting applications listed by university (rather than by
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sickness absence and annual leave records. Data input and export to prepare information for monthly management reports and graphs. Regularly review and monitor the efficiency and accuracy of current systems
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Details Bacteriophage are potentially the most numerous biological entities on planet earth. Their diversity and ability to reveal novel biology as well as their potential to be developed as novel
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general admin support by maintaining and updating records, databases, filing systems, phone/email lists and committee terms of reference and membership lists and assisting with the organisation
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infrastructure inspection tools. Working in well known internationally acoustic group at the University of Sheffield, you will embark on developing an approach of remote acoustic sensing of defects invisible
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require metrics that predict how well a given hearing aid algorithm will perform for a specific user in a particular acoustic environment. Existing approaches often rely on oversimplified assumptions about
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Overview Join a world-leading team developing life-changing treatments for people with MND Working in multidisciplinary Better Outcomes for MND team based at the Sheffield Institute for Neuroscience
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Development of biofidelic test-beds for assessing human interactions School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof M Carre, Prof R Lewis, Dr J Rongong
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successful academic outcome and develop skills for achieving and maintaining a healthy life. As an Advanced Nurse/Clinical Practitioner you will be a registered healthcare professional with your digital badge
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-identified scans, records and sensor feeds to answer questions such as: Can we predict a patient’s response to treatment without ever seeing their raw file? Can an algorithm learn the warning signs of trouble