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-organising reaction networks and the emergent complexity in such systems form powerful reservoir computers capable of non-linear classification, times-series prediction and forecasting, on a par or even
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by the Ada Lovelace Centre and the University of Birmingham. This interdisciplinary project is ideal for candidates with a background in physics, materials science, chemistry, or computational science
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an increasingly complex development environment. Areas to consider that impact the modelling are: Framework Language Process How wide / how deep i.e. what do we model and why? How much provides a good answer i.e
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Application deadline: 15/08/2025 Research theme: Computer Science No. of positions: 1 Eligible for: UK This 4-year PhD project will be funded by DLA studentship and is open to UK students
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project within an NHMRC-funded program focused on dementia research. Using a systems biology framework, the project will integrate genomic and lifestyle data to identify key molecular pathways and risk
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and synthesising robust, scalable electrocatalysts – including single-atom catalysts and molecular complexes – with tailored active sites for alcohol formation. Engineering reactors that support stable
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treatment programs) in Denmark at the PhD Programme Social Science and Business. The position is available from 1 October 2025 (or as soon as possible thereafter). The research project The PhD position offers
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
engineers detect faults earlier, track system degradation, and make better-informed maintenance decisions. But how can we turn this complex information into something reliable, explainable, and actionable
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opportunities for personal development and training, e.g. through an extensive range of training courses; a structured program of continuing education and networking opportunities specifically for doctoral
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project: Computational methods for complex SV detection using sequencing data Main supervisor: Kristoffer Sahlin, ksahlin@math.su.se . Co-supervisor: Adam Ameur, adam.ameur@igp.uu.se . In the Department