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, analytical and experimental techniques to investigate potential fuel additives to understand the mechanical, chemical and environmental impacts. We are looking for an enthusiastic and self-motivated person
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biosynthetic machinery Applying novel GAG analytical technologies to investigate how changes in GAG structure and organisation drive and/or respond to shifting developmental stages. Working Environment: Based
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UKHSA surveillance datasets to see if OTC sales can be used to monitor GI infection activity and better predict outbreaks. The PhD offers the unique opportunity to develop skills in analytical
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. Comparison with known analytic methods and established Markov models will be made wherever possible. Expected outcomes include a unified non-Markovian framework for time series analysis, a suite of relevant
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, usability, and insight into leakage dynamics across diverse constructions. Research Objectives The project is structured around three synergistic work packages: Descriptive Analytics: You will conduct a
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of the GAG biosynthetic machinery Applying novel GAG analytical technologies to investigate how changes in GAG structure and organisation drive and/or respond to shifting developmental stages. Working
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scientific discipline. • First-rate analytical and numerical skills, with a well-rounded academic background. •Demonstrated ability to develop precision mechanical devices/mechatronics •Ability to develop kinematic and
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systems of differential equations. The resulting models will be analysed with analytical tools from applied mathematics and numerical studies in the Julia programming language. The successful candidate
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are seeking talented candidates with: First or upper second-class degree in Robotics/Mechanical/Cybernetics/Mechatronics /Computer Science or related scientific discipline. First-rate analytical and numerical
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analytical and numerical skills, with a well-rounded academic background. •Demonstrated ability to develop precision mechanical devices and mechatronics •Ability to develop kinematic and/or dynamic analysis