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Field
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manufacturing (CfAM) and advanced bio-printing (Additive BioFabrication Laboratory), and will provide experience with new and advanced 3D-printing equipment not available elsewhere. This project is aligned with
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(CfAM) and advanced bio-printing (Additive BioFabrication Laboratory), and will provide experience with new and advanced 3D-printing equipment not available elsewhere. This project is aligned with
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or tuition contributions may be available from the host department based on academic merit and alignment with departmental priorities. The position is open to both UK/Home and international applicants.
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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, will be trained on simulation data to create dynamic, adaptive control systems that optimise operation in real-time across multiple variables. This research will deliver a validated roadmap to 60
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deadline: See specific DC application Starting date: See specific DC application. Latest 1st March 2026 Collaborating institutions: Multiple European universities, research centres and industry covering
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ceramics (i.e., avoid multiple re-heating steps)Understand the basic science driving low energy firing is an essential requirement to develop facile and scalable processing routesThe research deeply engages
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the systems-ML stack. This makes a cohort-based programme vital, treating ML Systems as a holistic discipline. Cohort interaction, and integration, give students real experience across multiple systems
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business needs while pushing technological boundaries. Your research will deliver transformative impacts across multiple industries by creating implementable solutions to longstanding operational challenges
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manufacturing (CfAM) and advanced bio-printing (Additive BioFabrication Laboratory), and will provide experience with new and advanced 3D-printing equipment not available elsewhere. This project is aligned with