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. Our group works closely with several experimentalists in SOPA (Prof Michael Fuhrer, Assoc Prof Mark Edmonds, Assoc Prof Agustin Schiffrin). Our work on field-tunable 2D materials feeds low-energy
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. Interdisciplinary collaboration: You’ll be part of the MESA+ Institute embedded in the world-class NanoLab infrastructure, and collaborate closely with Department of Applied NanoPhotonics, and Centre for Brain
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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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the results in peer-reviewed journals and at international conferences. Your profile Master's degree in physics, materials science, chemistry, nanoscience or a closely related field. Strong interest in optical
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performance, adaptability, and robustness of these materials. Emerging evidence suggests that aperiodic lattices—ordered yet non-repeating structures inspired by quasiperiodic tilings—can exhibit near-isotropic
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to preserve the structure and functionality of active electrode materials, reducing energy consumption and maximising material value. The successful candidate will explore pathways for recovering, regenerating
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for materials discovery. The position suits a candidate with strong programming skills, from computer science, AI, physics, chemistry or materials science, who wants to work at the interface of agentic AI
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with careful attention to detail and the ability to work independently. The position pays $25/hour for a total of 20 hours of work. Qualifications: PhD Pay Range Disclosure The University's pay ranges
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Title: Dynamic Processes in Organic Functional Materials Supervisor: Professor Paul McGonigal Start date: 1st October 2027 Applications are invited for a DPhil studentship in Synthetic andPhysical
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and functional materials. UV photopolymerisation, and more recently LED technologies, enable rapid, localised and energy-efficient processes. Recent developments in UV LEDs at different wavelengths, as