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interdisciplinary research skills in statistical analysis, data visualisation, advanced programming, writing and oral presentation, and receive training to enhance transferable skills and employability. Person
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on the topic (2,4). Training and Development Training will maximise future employability in academia and industry: Programming and geospatial data analysis using Python/R. Machine/deep learning techniques
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change accelerate, we urgently need smart, evidence-based tools to plan, manage, and protect our marine ecosystems. At the forefront of this innovation is machine learning. Its ability to process complex
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someone with previous experience in programming, and an interest in biogeochemistry, but do not necessarily require environmental science as a first degree. Previous laboratory experience is desirable but
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strong numerate background. Prior experience of mathematical or statistical programming is highly desirable. Informal enquiries concerning the project are welcomed by the primary supervisor. Entry
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measurement; Measurement of related tracers (e.g., Radon); Programming (e.g., R, Python) for advanced atmospheric time-series analyses, including machine learning; Skills for presenting research at scientific
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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