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mobile genetic element found in the honey bee pathogen Paenibacillus larvae. Specifically, you will work to develop and validate methods for assessing the molecular functioning and fitness effects
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the “Inverse Problem” component of the project: developing and validating a satellite-based pancake-ice detection algorithm using ICESat-2 wave-damping observations within a Bayesian inversion framework
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immunofluorescence. • Experience with imaging software (e.g., ImageJ) and data analysis. • Organised, methodical, and proactive, with excellent attention to detail and a "can-do" attitude. Further details
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closely related quantitative field. • Have experience using statistical software (R, Python, SPSS, Stata), regression analysis, and statistical modelling are required. Preference will be given
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Biochemistry, Structural Biology, or a closely related subject. To be successful in this role you will have excellent communication skills and written English, strong quantitative and data analysis skills