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Applications are open The PhD project is part of a collaborative project: ‘A “virtual market” for analysing the uptake of energy efficiency measures in residential and commercial sectors’, funded by
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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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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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explores how people of different ages play together, focusing on the experiences and perspectives of all participants. Working within a broader research program, the candidate will collaborate with
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factors involved in the onset and progression of dementia. Advanced computational methods, including bioinformatics pipelines and machine learning, will be employed to uncover putative biomarkers and
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group of PhD researchers who will tackle the most pressing questions in Machine Learning while ensuring AI serves humanity responsibly. You'll work within one of our specialised research themes, each
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applicant will generate high-impact research by applying state-of-the-art deep learning, molecular modelling, and GPCR pharmacology to accelerate drug discovery for dementia treatment in postmenopausal women
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for alternative analytical approaches for vaccine–antigen quantification. You will then learn current industry best practice methods involving ELISA assays and biosensor technology at Zoetis before developing and
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Background Scholarship code: IND-25122 Expressions of interest - open until filled. This is an industry-linked PhD scholarship. This scholarship is created by La Trobe University in collaboration
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collaboration from industry partners AgriTech Solutions and Hydrotech Monitoring Pty Ltd (trading as HTM Complete), both leaders in agricultural technology and decision-support systems across Far North Queensland