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in this programme will generate evidence-based outcomes for technology adoption, collaborative frameworks between industry and academia, and practical roadmaps for transitioning towards sustainable and
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(SMEs) in the health and life sciences (H&LS) sector to embed and accelerate sustainable manufacturing in their businesses. Integrated research in this programme will generate evidence-based guidance
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experts, building a powerful, dual-skill profile. Completing this project will establish you as a leading expert in industrial AI and computer vision, highly sought after in the growing Smart Manufacturing
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Ghorbani, S., Wloka, C., Etemad, A., Brubaker, M. A., & Troje, N. F. (2020). Probabilistic character motion synthesis using a hierarchical deep latent variable model. Computer Graphics Forum, 39(8
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. The programme consists of four themes, covering all disease areas: Theme 1: Diagnostic and prognostic indications Timely identification of disease strongly influences the outcome and the cost of healthcare, but
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funded PhD studentship as part of TRACE (Technological Revolution towards an Agri-food Circular Economy), a €5.89m cross-border project supported by the European Union’s PEACEPLUS Programme and managed by
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https://www.poliproductions.co.uk/about https://www.costarnetwork.co.uk https://www.studioulster.com https://wearealbert.org https://juliesbicycle.com/our-work/bfi-sustainable-screen-programme
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Development of an docetaxel-loaded implantable device for the localised treatment of prostate cancer
drug delivery technology designed for the sustained release of chemotherapy directly into cancer tissue thereby improving clinical performance. Prostate cancer is one of the most common types of cancer