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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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Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
of the Bacterial Cell Envelope – From Molecular Structure to Metabolic Function: The cell envelope is the interface between a bacterial cell and its environment. MACSYS is currently modelling the structure and
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field). Additionally, experience in quantitative and/or qualitative research is preferred. The project is interdisciplinary and therefore, applications are welcome from a range of disciplines, including
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We invite applicants for a funded PhD that will aim to create a fully functional and commercially viable online Sustainable Eating Quiz. The food system generates about 35% of total global man-made
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Centre for Epigenetics (ACE), the South Australian immunoGENomics Cancer Institute (SAiGENCI) is inviting applications for a Level A Researcher in the field of cancer development and stem cells. SAiGENCI
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CSIRO IPhD Scholarship - Investigating the interactions between sulfide minerals and in-situ recovery fluids for sustainable copper mining The CSIRO Industry PhD Program (iPhD) is a four-year
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from an online group. Gen Z, being digital native, is more vulnerable to social media addiction and cyberbullying than any other age cohort. Increased use of social media during the pandemic has seen a
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energy projects. About 2XE 2XE is an award-winning South Australian consultancy committed to guiding companies towards sustainable growth and achieving net-zero emissions. Leveraging a robust blend of
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For better or for worse, Generative AI is changing our world. A key challenge in Generative AI is many-shot jailbreaking—where a language model, despite being explicitly trained to reject harmful
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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