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. • be located at the agreed project location(s) and, if required, comply with the university’s external enrolment procedures. Selection criteria Skillset: Proficient in Python, machine learning, 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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through publications and presentations at leading conferences. This project will be undertaken in collaboration with Dr Feras Dayoub of the Australian Institute for Machine Learning, and Advanced Systems
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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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Indigenous students with unique professional development opportunities that combine academic growth, industry engagement, and community impact. Guaranteed Industry-Based Learning (IBL) placements ensure
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-performance computing (HPC), Bragg Crystallography facility, and Adelaide Proteomics Centre. Our collaboration with Monash University further extends our access to advanced 300 kV Titan Krios and Helios 5 UX
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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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into fundamental molecular events. At the same time, access to translational pipelines will enable the candidate to apply their learnings in a meaningful way, revealing novel therapeutic targets critical for cancer
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deep learning. The purpose of this scholarship is to support a PhD student to contribute to the advancement of infrastructure monitoring technologies with strong industry collaboration. Student type
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AI & Cyber Futures Institute - Charles Sturt University | Bathurst, New South Wales | Australia | about 2 months ago
, as is a commitment to learning and advancing in these areas. The successful candidate will have the ability to work with real time industry tools, applying data-driven insights to tackle agricultural