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an individual Resistant, Tolerant, or Susceptible (R/T/S) to a virus? That is the key question we aim to answer in this PhD study. We have gathered data on viral outbreaks over ~20 years and sequenced hundreds
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atmosphere (1). Research Methodology: The primary objective of this PhD studentship is to develop near real-time capability for top-down ffCO2 quantification, based on synchronous changes in atmospheric CO2
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for fieldwork in South America. Training and Skills Development This PhD will provide comprehensive training in: Molecular techniques: DNA extraction, PCR, and next-generation sequencing library preparation
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across different imaging devices, including future sensors with unknown spectral sensitivities. Training The student will be based at the Colour & Imaging Lab at the School of Computing Sciences which has
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, multidimensional datasets is transforming marine ecology and redefining how we detect and respond to ecosystem change. Methodology This PhD will place you at the forefront of this emerging field. You will address a
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supervision across the Schools of Chemistry, Pharmacy & Pharmacology and of Environmental Sciences, gaining experience in both laboratory and computational approaches. You will benefit from two 3-months
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observations and modelling of the physics and biogeochemistry of Antarctic shelf seas. You will gain experience in computer coding, statistics for environmental science, working with and piloting autonomous
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NERC. Person Specification We seek an enthusiastic individual with a degree in geoscience, physical sciences, or computer science. Numerical literacy and experience with coding tools (Matlab or Python
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. Communication of scientific findings through publications and conferences. Person Specification A highly motivated candidate with: A degree or equivalent in numerate, computational, or environmental subject areas
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strong scientific interests and self-motivation. They will have a degree in physics, mathematics, oceanography, meteorology, or a related science with good computing and numerical skills. Entry