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electric machines for future defence and aerospace propulsion systems. The research will explore innovative machine topologies and advanced multi-physics design methodologies to enable electric machines with
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Grant Agreement No. 101312169. Working tasks: The PhD-project DC14 focuses on the development of an assisting tool for electrical discharge machining (EDM) to gain deeper knowledge on machining states and
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physiological signal. This MSc by Research will investigate a fundamentally different question: “Can low-energy electrical measurements provide a reliable estimate of changing fluid volume within a cardiovascular
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sectors. Process driven research activities are performed in the field of chemical and biochemical systems, mechanical and electric systems and system networks. Typical product sectors include biobased
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PhD Studentship: Robust, Certified, and Scalable Federated Machine Unlearning for Privacy-Preserving AI About the Project As federated learning systems become increasingly embedded in high‑stakes
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, electrical machines, power electronics, dielectric/insulation materials, or related areas would be advantageous. Knowledge of numerical/FEM simulation tools such as COMSOL Multiphysics and MATLAB. Programming
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Doctor of Philosophy (PhD) in Machine Learning for In Situ Materials Characterisation Job No.: 698995 Location: Clayton campus Employment Type: Full-time Graduate Research Degree: 3291 - Doctor
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04.08.2026, Academic staff We are hiring a PhD researcher to develop water-based electric propulsion technologies for future spacecraft. The project will investigate how water can be stored
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University. Student type Current Students Faculties and centres Centre for Aboriginal Studies Course type Pathways to undergraduate Specifically for Aboriginal/Torres Strait Islander Students Citizenship
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Can electricity replace acids