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Design and Manufacturing Engineering to Tackle Global Sanitation Challenges - MSc by Research or PhD
optimization. The research focuses on creating efficient design workflows, validating multiple additive manufacturing approaches, and developing scalable production methods that can support global deployment
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scintillator-based radiation sensors combining multiple materials with complementary functions, offer a promising route to overcome these limits and achieve unprecedented timing resolution (sub-70ps), enabling
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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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technically sophisticated and genuinely user-friendly. This project aims to develop a comprehensive AI-driven software platform for smart sanitation systems that serves multiple user groups through tailored
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reusable launchers, autonomous robotics, and advanced materials could redefine how we design space structures. The ability to remotely assemble orbital systems from multiple launcher payloads would allow
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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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Multiple self-funded PhD positions are available in Modelling and Simulation (M&S). The project will aim to mature software repositories describing the biomechanics of the human brain. The M&S tools
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that can be validated with experiments and bottom-up models at multiple scales in order to predict the macroscopic response. Hence, this research will investigate the degradation of metallic materials under