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from a technical and scientific perspective. The Ph.D. candidate will develop methods for uncovering DNS infrastructure dependencies at scale, relying on active measurements and graph-based analysis
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processes. This has created a need to offer doctoral candidates a broad education and experience in both experimental molecular biology and data analysis, with possible specialisations in genomic and
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of marginalised communities through documents, interviews, and focus groups to understand their views on health data governance. Additionally, you will also be responsible for managing some organisational elements
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, through clever chemistry that attracts CO2 to the surfaces of 3D spongelike materials (such as metal-organic frameworks, or MOFs); and decarbonise the energy sector by designing new catalysts that will
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scientists. * Excellent oral and written communication skills. Preferred Qualifications * Familiarity with common NGS analysis tools. * Familiarity with tensorflow and/or pytorch.  * Demonstrated ability
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analysis of dynamic systems of oligosaccharides; biophysical studies using spectroscopy (NMR, UV-Vis, fluorescence and CD spectroscopy) to investigate conformation, binding phenomena and self-assembly
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Matlab, Python and C/C++ are preferred. Strong interpersonal skills and the capacity to work and learn independently will be required. English Language IELTS 6.0 Overall (with no individual component below
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analysis of individual genes, RNAs, proteins, and metabolites is often complemented by an analysis of cellular systems in their entirety. However, this development also poses a major challenge, namely the
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programming experience (preferably in Python). If English is not your first language, provide evidence of proficiency through: A minimum IELTS average score of 6.5 and a minimum of 6.0 in each component. OR A
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motion) Pose tracking and behavior segmentation with tools like DeepLabCut, MoSeq, and Kinect-based systems Longitudinal analysis of behavior from early postnatal to adolescent stages in