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interested in connecting spatial and spectral information to understand complex materials systems at the molecular level with machine learning. PhD Student A will work with tumour sections to develop multiple
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active sites), in vitro and in vivo enzyme screenings, electrochemistry, and machine learning-assisted directed evolution. As part of this project, you will collaborate closely with PhD students and
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are looking for a highly motivated and skilled PhD researcher to work on graph-based machine learning surrogates of wind energy systems. Our goal is to accelerate flexible fatigue load estimation
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The Australian Institute for Machine Learning (AIML) offers new PhD scholarship opportunities in Industrial AI. These full-time scholarships support students undertaking their PhDs in AI and machine
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of dehydration using a low-power radio-frequency (RF) sensor. The research objectives include design optimization to improve wearability, robust data acquisition using machine learning and establishing correlation
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well organized, structured, self-driven and enjoy interacting and collaborating with colleagues including PhD students, postdocs, and you are expected to take part in supervision of BSc and MSc students
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research group with a broad interest in plant biomechanics, ecology, development and evolution. A supervisory team comprising a plant scientist, a cell biologist and a physicist, as well as two postdocs with
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scientists, cell biologists, bioimaging specialists and physicists, as well as a postdoc with a specific background pitcher plant development, transcriptomics and bioinformatics. Supported by this expert team
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European CLARIFY project and continues this research with a postdoc, PhD student and lab technician. You will closely collaborate with clinicians to define clinically relevant questions, digitize pathology
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. Through application of a representative learning design framework this project will explore how representative are the training activities undertaken in different in game phase (set play / offensive