566 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" positions at University of Sheffield
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How does a molecule walk? Computer simulations of molecular machines in action School of Mathematical and Physical Sciences PhD Research Project Directly Funded UK Students Prof Sarah Harris, Dr
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people in earthquake conditions to military operations in unknown and changeable environment. Such sensor networks have extended their territory to industrial applications, such as energy management
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and coding using either Python or Mathematica are essential. Experience with a computer algebra system such as Mathematica is an advantage. We are also looking for good written and verbal communication
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. Visit http://www.sheffield.ac.uk/sgs to learn more. Funding Notes First class or upper second 2(i) in a relevant subject. To formally apply for a PhD, you must complete the University's application form
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candidates for this project should have a strong background in Applied Mathematics, Engineering, Physics or other related disciplines. Full details of how to apply can be found at the following link: https
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between the brain signals of different subjects. The aim of this project is developing new adaptive and machine learning algorithms to successfully decode brain signals across subjects. The prospective
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the Light Microscopy Facility (https://www.sheffield.ac.uk/lmf). Wild-type and mutant lines will be crossed to transgenic lines of interest for live fluorescence imaging. There will also be the opportunity
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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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, numerate subject (such as maths and physics), including Matlab programming. Full details of how to apply can be found at the following link: https://www.sheffield.ac.uk/acse/research-degrees/applyphd
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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