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communication, and applied security research. Applicants are expected to hold (or be close to completing) a minimum of an upper second-class undergraduate honours degree (or equivalent) in Computer Science
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Training in Engineering Solutions for Antimicrobial Resistance. Further details about the CDT and programme can be found at AMR CDT website Applications should be submitted by 12th January 2026.
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applicants may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How To Apply Please read and complete this document as
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applicants may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How To Apply For information on how to apply, please
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learning/AI, geoarchaeology, environmental science, or computer science would be beneficial, but is not required, depending on equivalent experience. Funding notes: This project is funded by the European
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are fundamentally limited by a "one model for one task" design philosophy. This approach incurs prohibitive engineering costs and yields brittle solutions with poor generalisation to new network conditions, trapping
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Student Development The successful applicant will gain expertise in: Biophysical imaging (AFM, microscopy) Microbiology and molecular biology RNA sequencing and data analysis Interdisciplinary collaboration
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for Doctoral Training in Engineering Solutions for Antimicrobial Resistance. Further details about the CDT and programme can be found at AMR CDT webiste Applications should be submitted by 12th January 2026.
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will deliver a novel diagnostic platform capable of detecting respiratory infections and resistance markers at the point of care with unprecedented sensitivity and speed. This technology could
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behaviour in a practical, real-time monitoring system requires advances in both sensor engineering and behavioural data interpretation. This PhD project aims to develop a next generation environmental