515 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" uni jobs at University of Sheffield
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BSM processes. This will involve taking a lead role in developing dedicated software frameworks, including the implementation of machine learning techniques. A long-term attachment (6-12 months) and
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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line
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Digitalising populations of structural systems using machine learning (S3.5-MAC-Dardeno) School of Mechanical, Aerospace and Civil Engineering PhD Research Project Competition Funded Students
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macropinosomes to retrieve membrane proteins and therefore sustain both immune and cancer cell function. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying
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will also be considered. References Korsós et al., ApJL 802 L21 (2015) https://iopscience.iop.org/article/10.1088/2041-8205/802/2/L21 Korsós, Chatterjee, Erdélyi, ApJ 857 103 (2018) https
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evolution of rhizobia in the lab and in plant mesocosms alongside omics technologies such as genomics and transcriptomics and analysis of pre-existing datasets. You will learn techniques such as sterile
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Investigating how DNA damage responses combat infections by the typhoid pathogen Salmonella enterica
Srour et al. 2025, EMBO Mol Med (https://doi.org/10.1038/s44321-025-00347-8) ElGhazaly et al., 2023, Cell Reports (https://doi.org/10.1016/j.celrep.2023.113181) Ibler et al. 2023, Nat Commun (https
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the field to inform farmers of varying soil conditions through traditional remote sensing techniques. For further Information, please email p.stowell@sheffield.ac.uk or look at the University’s website: https
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transductions. Funding Notes Self-Funded Students only References https://sites.google.com/sheffield.ac.uk/peden-lab https://etheses.whiterose.ac.uk/28686/ View DetailsEmail EnquiryApply Online
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The effects of micro-machining operations on structural integrity of biomaterials used in dental applications School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded