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PhD Studentship: Taking the forever out of forever chemicals –destruction of per- and poly fluoroalkyl substances (PFAS) in mixed matrices Research by the team currently focuses on different aspects
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to develop a high-performance disposable analytical tool for the on-site detection of folic acid in several food matrices. This technology is based on our recently developed wireless and batteryless, near
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leverages structural-functional data to design, synthesise, and evaluate these compounds in relevant experimental models, including food matrices. These innovative compounds have dual potential: (i) as
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matrices. Task 1.3: Selectivity and Interference Analysis (M19– M42) The selectivity of the sensor will be tested in solutions containing DA and common interferants such as uric acid (UA), ascorbic acid (AA
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-tuning only a small set of low-rank matrices for each agent role, drastically reducing GPU memory and training time while preserving the model's pre-trained knowledge. The primary outcome of this research
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volumes can be dealt with using Discrete Cosine Matrices (DCM) and quaternion-based orientation modelling. Mining deposits are rarely isotropic, their geometry reflects geological processes such as folding
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compressible gas dynamics, heat transfer, free-surface/melt behaviour, and mass transfer driven by phase change, within a GPU-accelerated solver to reduce simulation turnaround times. You will develop and
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compressible gas dynamics, heat transfer, free-surface/melt behaviour, and mass transfer driven by phase change, within a GPU-accelerated solver to reduce simulation turnaround times. You will develop and
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the forever out of forever chemicals –destruction of per- and poly fluoroalkyl substances (PFAS) in mixed matrices PhD studentship in Light Scattering by Single Particles Relevant for Atmospheric Research Join
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on large annotated datasets. Memory-efficient deep learning: Model compression, pruning, quantisation, selective memory replay, and efficient training strategies. Energy-efficient deep learning: Methods