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from visual and auditory cortices recorded over multiple days Apply and adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural
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an adhesive heavy application, and to find methods for End-of-Life disassembly. Battery pack construction uses adhesives to fix multiple cells in place, creating a block of battery modules. The adhesive has
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, which is not possible with current systems. It aligns with key STEM themes and EPSRC’s strategic focus on ‘Engineering’, ‘Health and Medical Technologies’, and ‘AI, Digital, and Smart Applications
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environment, ensuring that research outcomes directly align with future aviation applications. As part of the PhD, you will have opportunities for placement at Airbus. The main impact of this PhD will be
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, you cannot apply for multiple studentships on one application. You are welcome to apply to other studentships at the same time, as long as you cite the relevant code on each application (e.g. ReNU25_7
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sequencing technologies - including metagenomics and transcriptomics - to explore the dynamic interplay between human gene expression and microbial communities. The successful candidate will develop and apply
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will generate a wide range of contemporary high-resolution next-generation sequencing and array-based genomic and epigenomic datasets across large cohorts of human tumours and experimental models
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contemporary high-resolution next-generation sequencing and array-based genomic and epigenomic datasets across large cohorts of human tumours and experimental models, alongside complex drug screening, efficacy
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aligned subjects The Project start dates: October 2025 – Home students only January 2026 – Home and International students Supervisors: Aligned programme of study: PhD in Chemical Engineering Mode of study
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consider the multiple health and other impacts when deciding on appropriate action. This PhD studentship will conduct an assessment of the impacts of policies aimed at improving home energy efficiency