408 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"SciLifeLab" PhD positions in United Kingdom
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collaboration with process engineers (Adrian Oehmen, Nasim Amiralian, both UQ) to determine adsorption capacity, regeneration efficiency, and long-term stability, generating the performance data required
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TypeFixed-termWorking TypeHybridAvailable for SecondmentNoClosing Date30-Apr-2026JD_Param11NoJD_Param12No Two 3.5 year PhD studentships in Artificial Intelligence in Medicine, or Health Data Science, funded
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energy demand. Combining applied mycology, food safety modelling, precision agriculture and Net Zero energy systems, the research will deliver energy-efficient, data-driven grain storage solutions
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expression in the tumour. The models will be calibrated against pre-clinical data and compared to literature models that are based on ordinary differential equation systems without a description of spatial
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techniques employed include high-throughput cell based screening, flow cytometry and preclinical treatment models. Informatic approaches include data mining and manipulation of large pharmacogenomic matrices
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Studentship Information Supervisor: Professor Ian Fisk Secondary Supervisor: Dr Vincenzo di Bari, Dr Louise Hewson, Mui Lim Subject Area: Food Science Research Title: Sodium Reduction in Coated
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. Further details about the project, eligibility and application process can be found in the Further Information document. PhD studentship: Recording nature and writing the self: time, entomology and the
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to learn from. Augment Data with Generative AI - You will use physics-constrained generative models (Diffusion models/GANs) to create a diverse library of synthetic microstructures, improving model
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‑bounded turbulence. This short, intensive 9‑month position offers an exciting opportunity to advance fundamental turbulence research using DNS/LES and data-driven optimisation techniques. In this role, you