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numerical modelling framework to simulate how light and heat interact with the target body tissue, while also incorporating neural signalling dynamics to explore how light-based stimulation affects
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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manufacturing sectors into valuable products. The scholarship will support one student to work on the development of novel biomass based adsorbents for CO2 capture. A combined experimental and simulation methods
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your EOI, nominate Dr Steph Hutchison as your proposed principal supervisor, and copy the link to this scholarship website into question 2 of the Financial details section. About the scholarship
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results accurately and draw meaningful conclusions to inform further research and process improvements. Background in modelling and simulation using simulation software. Background in Techno-economic
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: The proposed project aims to enhance the sustainability and transparency of the battery materials supply chain by integrating Environmental, Social, and Governance (ESG) criteria and Life Cycle Assessment (LCA
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recycling: Project 1 (2 PhD students): Cost-Efficient Direct Recycling for Metal Oxide Cathode Materials – These projects focus on developing low-cost, scalable strategies for the direct recycling and
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, especially in ultracold quantum gases or condensed matter theory Proven analytical, computational, and modelling skills Experience with numerical simulations of quantum or many-body systems A deep curiosity
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transcript, a research proposal addressing the scholarship topic, using the required research proposal template , as well as a writing sample (e.g. copy of an article/essay/thesis you have written