415 phd-computational-"IMPRS-ML"-"IMPRS-ML"-"IMPRS-ML" positions at Monash University in Australia
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seeking a leading researcher to advance a program in Applied Clinical Data Science, Machine Learning and AI. This role offers the chance to lead high-impact projects, mentor emerging researchers, and
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is highly complex. For the proposed PhD project, experimental data are already available that bring together maps of orientations of such crystals together with the deformation pattern generated during
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peer-reviewed publications, while providing senior-level expertise to support and mentor internal teams. A vital responsibility includes guiding emerging science-practitioners (Clinical Psychology PhD
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ecosystem interactions. If used wisely for decision-support, these technologies can help select and implement effective policies. This PhD project, jointly offered by Monash University (Australia) and
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The proposed PhD project aims to build a machine learning/deep learning-based decision support system that provides recommendations on precision medicine for paediatric brain cancer patients based
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, fabricate structures at the Melbourne Centre for Nanofabrication, and measure their optical and electrical properties. The successful candidate will have a PhD in Physics, Materials Engineering, or a closely
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/ Phd qualification). These scholarships are not applicable to recipients of other scholarships from other countries or other scholarship providers *Minimum academic requirements to be considered
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. Amandeep Kaur, you will contribute to a vibrant research program centered on the design and development of novel fluorescent probes for super-resolution imaging—a powerful technique revolutionizing how we
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, you’ll bring: A PhD in a relevant field. Proven record of scientific excellence, originality and research independence. Commitment to team science, open, responsible research (FAIR data), and a
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This PhD project is part of a larger project that aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain