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develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung infection. As part of this work, the postholder will
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) and supply chain sustainability modelling. The successful candidate will work with Prof Lenny Koh (Deputy Director of IGNITE) to deliver C3.2 (Supply chain optimisation and LCA). C3.2 will build from
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, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn't match perfectly with this role's criteria, your contribution is valuable
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of Biosciences Technical Manager, and working closely with the Facilities Governance Team, you will provide specialist input into the business model and future planning for the Facility. Educated to a minimum of
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but not limited to: media, solutions and buffers; yeast and bacterial cultures; mammalian cell culture; model organisms; DNA, plasmids and PCR; electrophoresis gels; cell extracts; proteins and enzymes
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clinical checks—when interventions can have the greatest impact on patient outcomes. However, in current practice, diagnosis is often delayed until the patient arrives at hospital, by which time the optimal
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. These results will be used to improve implant designs, as part of a UKRI funded project that aims to deliver novel validated computational models to predict bone ingrowth in porous orthopaedic implants. The ideal
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of Sheffield and Nottingham, and the Alan Turing Institute. The wider focus of this research programme is to develop both physics-based and data-driven models of heart function and blood flow through
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. This will involve working within our team to establish new brain-invasive orthotopic patient-derived xenograft (PDX) models of glioblastoma using cells from within our within the Sheffield Living Biobank
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develop a non-invasive method that eliminates the need for additional sensors or frequent recalibration. By training sophisticated AI models on extensive clinical datasets of PPG waveforms, we aim