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Field
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. Literature review of technologies and commercial market scanning. Modelling, simulation and data management. Design and analysis of hardware and software. Coding, debugging, and troubleshooting. Testing
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develop ontologies of software vulnerabilities in the edge computing environment. Vulnerability Detection: Monitor and/or analyse source code (and data), software behaviours, and software environment (e.g
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involve performing numerical simulations to study magnetic fields in the cores and crusts of neutron stars, using and extending one or more existing codes, but also developing entirely new codes
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Analyse and interpret qualitative data using appropriate methods (e.g. thematic analysis) Use qualitative software (such as NVivo) to manage and code data Apply knowledge in a way that develops new
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code are encouraged as part of the application). Experience working with Unix-based operating systems, and tools for reproducible research (e.g. GitHub, Rmarkdown). Good communication skills and ability
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their application clearly which they are familiar with and their degree of expertise). Experience of geo-coded data analyses and Propensity Score Matching would also be relevant. Expert interviews will also form part
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HiPerBreedSim project. In this role, you will leverage recent advances in working with ancestral recombination graphs (ARGs) to develop algorithms and code for simulating population genomic data, including
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-based code optimisation. You will develop novel techniques that harness the power of machine learning to create optimisation strategies for compilers and memory management libraries for next-generation
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code are transparent, well-documented, reproducible, and openly shared with the scientific community. The role also offers opportunities to contribute to teaching and training activities across
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projects. Have an outstanding research record commensurate with their level of experience as demonstrated, for example, through an outstanding thesis, publications, conference presentations, code etc. Have a