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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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quantum media—and seeks to deepen our understanding of their behaviour in ultracold atomic gases and complex quantum materials. By harnessing ultracold atoms as highly controllable quantum simulators
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request a copy of your CV together with a cover letter outlining your relevant qualifications, experience, research experience, and reasons for applying for the scholarship. Shortlisted applicants will be
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• Strong quantitative and programming skills; experience with seismic data analysis or numerical modelling is highly desirable• Excellent written and verbal communication skills• Ability to work
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observational research (e.g., simulations) and/or lab or field experiments Experience with the analysis (e.g., sequential analysis, multilevel modelling) and interpretation (e.g., conference presentation
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Step 1: Expression of Interest: Before applying, prospective applicants must email the following to Dr Aliakbar Gholampour at aliakbar.gholampour@flinders.edu.au : A current CV A copy of your
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degree . In your EOI, nominate Associate Professor Angela Watson as your proposed principal supervisor, and copy the link to this scholarship website into question two of the financial details section
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to trick AI-based models, pay little attention to fake-normal data traffic generated by Generative Adversarial Networks (GAN). This PhD research will address a major vulnerability in AI based smart grids by
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), mouse models, fluorescence microscopy (confocal), genomics, epigenetics, cell biology and biochemistry techniques (e.g., RNA/ChIP-seq, mass spectrometry). Successful track record in conducting and driving
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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