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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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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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(optional). Person specification: Prior experience in computer coding (e.g., Python, SLiM), AI modelling, and understanding of evolutionary or conservation genetics / genomics is desirable. Good teamwork
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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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. Bioinformatics: Comparative genome analysis, detection of selection, and functional genomics, phylogenetics. Computational skills: UNIX/Linux, HPC computing, and programming in R and Python. You will gain hands
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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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Specification We seek an enthusiastic individual who is interested in marine ecology, computing, with some prior experience in programming and data handling, eager to communicate findings to wider stakeholders
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limited number of studentships are available for international applicants, with the difference between 'home' and 'international' fees being waived by the registering university. Please note, however, that
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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