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on such jets — although their detailed properties remain unexplored. In this project, we will develop new computational methods to compute and characterize these novel wave solutions, with particular emphasis
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in previously unrealised ways and places, enhancing device communication and functionality in the defence and security domain. The Studentship Starting ASAP or before 1st October 2027
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motivated students with a strong background in engineering or computer science. The ideal candidate will have: Strong programming and software skills. An awareness of machine learning theory and techniques
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for aerospace applications. The research aims to address a technological challenge with the potential to improve safety, reliability, and operational efficiency in future aerospace systems. The successful
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2027 Additional Funding Information This project is offered on a self-funded basis. It is open to applicants who are self-funded or who are in the process of securing external funding. A bench fee is
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, threatening global food security. We will identify the genetic and epigenetic changes associated with prolonged sub-culture of the blast fungus using comparative genome analysis and thereby define
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pathogens, which cause significant losses in crop yield each year. While controlling microbial pathogens is essential for sustainable agriculture and global food security, developing durable disease
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genome sequencing and single-cell approaches, as well as broader data integration across multiple omics data types. The role holder will apply their computational and bioinformatics skills to contribute
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year. The start date is October 2026. Only UK Nationals with a British passport can apply. The project is sponsored by MBDA and requires security clearance for the candidate. We recommend that you apply
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epidemiological data, genomic and surveillance data, and selected UK Health Security Agency (UKHSA), Food Standards Agency (FSA) and other food-related datasets. These data provide opportunity to quantify true