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processing and hybrid BCI design Machine learning (ML) Bioinspired control systems Neuroplasticity and motor recovery Real-time control of soft exoskeletons Your Role As a PhD candidate, you will: Develop and
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. Strong coding skills for programming neural networks, machine learning and machine learning software frameworks (e.g. PyTorch or Jax) is a must. The ability for creative and analytical thinking across
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which there exists extensive experience in the areas of machine learning, biostatistics, and medicine: Dr Yanda Meng and Dr Tianjin Huang (Machine Learning), Prof Yalin Zheng (AI in Healthcare), A/Prof
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hold an MSc degree in environmental science or ecology, with a proven expertise in data analysis, organizing and handling. Expertise in machine learning is a plus. A sound command of the English language
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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such as case weighting, anomaly detection, and model-based prediction (e.g., geostatistics and machine learning), using auxiliary geospatial or remotely sensed data. Quantifying uncertainty and correcting
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. He/she/they will learn and apply state-of-the-art molecular and cell biology technologies established in our team, ranging from in vivo disease models to multi-omics and single cell analysis
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evaluate them alongside newly developed approaches. Integrating methods such as case weighting, anomaly detection, and model-based prediction (e.g., geostatistics and machine learning), using auxiliary