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delivers high-impact teaching, research, and industrial collaborations. The project sponsor Dynex Semiconductor is a leading international high power semiconductor business, and has a manufacturing and R&D
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analytical methods for the analysis of linked data from electronic health records and genomic or molecular sources. Strong statistical skills (e.g. proficiency in R or Stata), along with excellent writing
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entire functions and showed that these are always bounded by simple closed curves. They also showed that, under certain conditions, the full Julia set is locally connected. Also, Rempe ([R], Acta Math
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, or the equivalent qualifications gained outside the UK. Experience in coding in both Python and R is essential.
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emerging to address the ‘broken system’ of antibiotic R&D. It focuses on the actors and stakeholders seeking to develop a radically altered antimicrobial innovation ecosystem by establishing alternative
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of technical excellence, SLB has heavily invested in technology development, and is supported by an R&D spend that since 2015 has annually averaged more than US$800M. The company thus strives to be
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Research theme: Nuclear thermal-hydraulics How many applications: 1 How to apply:uom.link/pgr-apply-2425 This project is co-funded by EDF R&D UK and the University of Manchester. Funding covers
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business datasets (e.g. ORBIS, Foreign Direct investment Data - UNCTAD) and appropriate experience with statistical software (e.g. Stata, R, Python). They will have a good understanding of, and interest in
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the simulation results. This work builds on our previous research on crosslinking at the substrate/polymer interface: Suzanne Morsch, Yanwen Liu, Kieran Harris, Flor R. Siperstein, Claudio Di Lullo, Peter Visser
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statistical and/or analytical software packages (e.g., SPSS, R, Tableau, Power BI, etc). How to apply Interested applicants should contact Dr. Stefan Birkett (s.birkett@mmu.ac.uk ) for an informal discussion