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privacy constraints, robust solutions are essential. This PhD project will develop methods for building reliable medical imaging models that generalize across distribution shifts without retraining
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disease patients using radiation therapy. The primary aim of this research is to develop real-time target tracking and/or dynamic imaging algorithms for implementation within radiotherapy and medical
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radiation therapy. The primary aim of this research is to develop real-time target tracking and/or dynamic imaging algorithms for implementation within radiotherapy and medical imaging. Within our research
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sustainable, electrified alternative to the Haber-Bosch process. You will design hybrid catalyst systems (heterogeneous and homogeneous), engineer innovative electrochemical reactors, and pioneer radical
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prototype testing, and field demonstration, partnering closely with industry to deliver contracted research outcomes that address real engineering challenges. Over the three-year appointment, you will build
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Australian Prostate Cancer Foundation (ACRF) Single Cell Proteomic Laboratory. The successful candidate should have a PhD in bioinformatics, computational biology, cancer genomics or a related field with
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“Revealing Order in Organic Semiconductors with Cryo-Electron Microscopy.” The successful candidate will apply and develop advanced cryo-electron diffraction and imaging methods to uncover structure–property
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of Engineering and contribute to industry-engaged research in construction materials and modelling. This role offers a rare opportunity to work across laboratory experimentation, scaled-up prototype testing, and
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hands-on experience with Python and ML libraries (PyTorch/TensorFlow) experience with signal/image processing or computer vision for video strong programming and data engineering skills Desirable
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coordinate data management processes, ensuring thorough analysis and reporting that drives research insights strengthen partnerships with key stakeholders, enhancing research collaborations and joint